Headquarters: London, UK; Ontario, CAN; Remote-Friendly, United States; San Francisco, CA About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.Applications are currently closed, we will update this page when they re-open. Anthropic Fellows Program overview The Anthropic Fellows Program is designed to foster AI research and engineering talent. We provide funding and mentorship to promising technical talent - regardless of previous experience. Fellows will primarily use external infrastructure (e.g. open-source models, public APIs) to work on an empirical project aligned with our research priorities, with the goal of producing a public output (e.g. a paper submission). In one of our earlier cohorts, over 80% of fellows produced papers. We run multiple cohorts of Fellows each year and review applications on a rolling basis. What to expect 4 months of full-time research  Direct mentorship from Anthropic researchers  Access to a shared workspace (in either Berkeley, California or London, UK) Connection to the broader AI safety and security research community Weekly stipend of 3,850 USD / 2,310 GBP / 4,300 CAD + benefits (these vary by country) Funding for compute (~$15k/month) and other research expenses Interview process The interview process will include an initial application & reference check, technical assessments & interviews, and a research discussion.  We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Compensation The expected base stipend for this role is 3,850 USD / 2,310 GBP / 4,300 CAD per week, with an expectation of 40 hours per week for 4 months (with possible extension). Fellows workstreams Due to the success of the Anthropic Fellows for AI Safety Research program, we are now expanding it across teams at Anthropic. We expect there to be significant overlap in the types of skills and responsibilities across the roles and will by default consider candidates for all the workstreams. Some of the workstreams may include unique assessment steps; we therefore ask you for workstream preferences in the application. You can see an overview of the current workstreams below: AI Safety Fellows AI Security Fellows ML Systems & Performance Fellows Reinforcement Learning Fellows The Anthropic Institute Fellows (Economics & Policy) This page is specific to one of the Anthropic Fellows Workstreams, see also the main Anthropic Fellows posting. Across the workstreams, you may be a good fit if you: Are motivated by making sure AI is safe and beneficial for society as a whole Are excited to transition into empirical AI research and would be interested in a full-time role at Anthropic Have a strong technical background in computer science, mathematics, or physics Thrive in fast-paced, collaborative environments Can implement ideas quickly and communicate clearly Strong candidates may also have: Strong background in a discipline relevant to a specific Fellows workstream (e.g. economics, social sciences, or cybersecurity) Experience in areas of research or engineering related to their workstream Candidates must be: Fluent in Python programming Available to work full-time on the Fellows program AI Safety Fellows Mentors, research areas, & past projects Fellows will undergo a project selection & mentor matching process. Potential mentors include: Sam Bowman Sara Price Alex Tamkin Nina Panickssery Trenton Bricken Logan Graham Jascha Sohl-Dickstein Joe Benton Collin Burns Fabien Roger Samuel Marks Kyle Fish Ethan Perez Our mentors will lead projects in select AI safety research areas, such as: Scalable Oversight: Developing techniques to keep highly capable models helpful and honest, even as they surpass human-level intelligence in various domains. Adversarial Robustness and AI Control: Creating methods to ensure advanced AI systems remain safe and harmless in unfamiliar or adversarial scenarios. Model Organisms: Creating model organisms of misalignment to improve our empirical understanding of how alignment failures might arise. Model Internals / Mechanistic Interpretability: Advancing our understanding of the internal workings of large language models to enable more targeted interventions and safety measures. AI Welfare: Improving our understanding of potential AI welfare and developing related evaluations and mitigations. On our Alignment Science and Frontier Red Team blogs, you can read about past projects, including: Subliminal Learning: Language Models Transmit Behavioral Traits via Hidden Signals in Data: Alex Cloud and Minh Le, et al., mentors including Samuel Marks and Owain Evans Open-source circuits: Michael Hanna and Mateusz Piotrowski with mentorship from Emmanuel Ameisen and Jack Lindsey For a full list of representative projects for each area, please see these blog posts: Introducing the Anthropic Fellows Program for AI Safety Research, Recommendations for Technical AI Safety Research Directions. Unique candidate criteria You might be a particularly great fit for this workstream if you: Are motivated by reducing catastrophic risks from advanced AI systems Have experience with empirical ML research projects Have experience working with large language models Have experience in one of the research areas mentioned above Have a track record of open-source contributions AI Security Fellows Mentors, research areas, & past projects Fellows will undergo a project selection & mentor matching process. Potential mentors include: Nicholas Carlini Keri Warr Evyatar Ben Asher Keane Lucas Newton Cheng On our Alignment Science and Frontier Red Team blogs, you can read about some past Fellows projects, including: AI agents find $4.6M in blockchain smart contract exploits: Winnie Xiao and Cole Killian, mentored by Nicholas Carlini and Alwin Peng Strengthening Red Teams: A Modular Scaffold for Control Evaluations: Chloe Loughridge et al., mentored by Jon Kutasov and Joe Benton Unique candidate criteria You might be a particularly great fit for this workstream if you: Are motivated by reducing catastrophic risks from advanced AI systems Have contributed to open-source projects in LLM- or security-adjacent repositories Have demonstrated success in bringing clarity and ownership to ambiguous technical problems Have experience with pentesting, vulnerability research, or other offensive security work Have a demonstrated willingness to do the "dirty work" that produces high-quality outputs Have reported CVEs or been awarded bug bounties Have experience with empirical ML research projects Have experience with deep learning frameworks and experiment management Logistics Logistics Requirements: To participate in the Fellows program, you must have work authorization in the US, UK, or Canada and be located in that country during the program. Workspace Locations: We have designated shared workspaces in London and Berkeley where fellows will work from and mentors will visit. We are also open to remote fellows in the UK, US, or Canada. We will ask you about your availability to work from Berkeley or London (full- or part-time) during the program. Visa Sponsorship: We are not currently able to sponsor visas for fellows. To participate in the Fellows program, you need to have or independently obtain full-time work authorization in the UK, the US, or Canada. Program Duration: The program runs for 4 months, full-time. If you can't commit to the full duration, please still apply and note your constraints in the application. We review these requests on a case-by-case basis. Please note: We do not guarantee that we will make any full-time offers to fellows. However, strong performance during the program may indicate that a Fellow would be a good fit for full-time roles at Anthropic. In previous cohorts, 25-50% of fellows received a full-time offer, and we’ve supported many more to go on to do great work on AI safety and security at other organizations. Applications and interviews are managed by Constellation, our recruiting partner. Constellation also runs the Berkeley workspace and provides program support for fellows working on AI safety and security; fellows on capabilities-focused projects are supported directly by Anthropic. All applicants currently use the same application portal but we are working to separate applications for safety/security and capabilities-focused projects in future rounds.   Applications are currently closed, we will update this page when they re-open. The below are Anthropic's policies for full-time roles. These do NOT apply to the Fellows Program.Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process. To apply: https://weworkremotely.com/remote-jobs/anthropic-anthropic-fellows-program-ai-safety-security

Headquarters: Remote (USA) PagerDuty, Inc. (NYSE: PD) is the global leader in AI-first digital operations. By automatically detecting, diagnosing, and remediating issues, the PagerDuty Platform orchestrates AI agents and automated workflows with context from over 750 integrations. Trusted by approximately two-thirds of the Fortune 100 and nearly half of the Fortune 500, PagerDuty is the industry standard for organizations scaling resilient, autonomous operations. Notable customers include Chipotle, Cloudflare, Docusign, Fox, Nvidia, Salesforce, Spotify, Zoom and more. We are growing rapidly and hiring top talent with leading AI skills across engineering, sales, product, marketing, and beyond as we build the leading digital operations platform.  PagerDuty is seeking an Account Manager to join our diverse, customer-focused team! As an Account Manager, you will serve as the primary point of contact for a portfolio of existing SaaS customers, partnering closely with cross-functional teams to deliver exceptional customer outcomes. You will maintain and grow customer relationships, drive product adoption, manage renewals, and identify strategic expansion opportunities that deliver measurable business value. This is an exciting opportunity to blend customer success and sales expertise to help customers realize the full potential of PagerDuty’s platform while driving revenue growth. The ideal candidate is a proactive relationship builder with strong commercial acumen, a passion for data-driven customer management, and experience with SaaS products and AI-driven insights. KEY RESPONSIBILITIES Own a portfolio of existing customers to ensure adoption, value realization, and retention. Develop and execute account plans that drive renewals, mitigate churn risk, and uncover expansion opportunities. Present and negotiate renewal proposals, structure multi-year options, and manage contract value through strategic account management. Monitor customer health using usage analytics, telemetry, and business insights to identify and address risks early. Collaborate cross-functionally with Legal, Sales Operations, and Renewals teams to ensure smooth contracting, forecasting, and reporting processes. Maintain strong product knowledge and deliver consultative guidance to drive configuration optimization and feature adoption. BASIC QUALIFICATIONS 7+ years of combined customer-facing experience, including Account Management, Customer Success, or Renewals. 4+ years of proven success managing renewals and growth within a SaaS environment. Experience using Salesforce (SFDC) and analytics tools such as Gainsight, Tableau, or Looker. Bachelor’s degree or equivalent experience. PREFERRED QUALIFICATIONS Demonstrated ability to leverage data analytics and health metrics to manage and retain customer accounts. Prior enterprise sales expertise leveraging MEDDPICC & Value Selling. Experience working with enterprise software customers or in a DevOps environment. Strong understanding of AI-powered tools and how they can be leveraged to drive efficiency and insight. Proven history of achieving revenue and retention goals through consultative account management. Self-starter with strong collaboration, negotiation, and problem-solving skills.  Hesitant to apply? We encourage you to submit your resume even if you don't meet every requirement. We value potential and consider each candidate's full professional story. Whether you're exploring a career change or taking your next step, we look forward to reviewing your application. If this just isn’t the right role or time - sign up for job alerts! Where we work PagerDuty operates a hybrid work model with offices in 8 major cities: Atlanta, Lisbon, London, San Francisco, Santiago, Sydney, Tokyo, and Toronto. While we offer flexibility within our established locations, we cannot employ candidates residing in: Location restrictions: Australia: Northern Territory, Queensland, South Australia, Tasmania, Western AustraliaCanada: Alberta, Manitoba, Newfoundland, Northwest Territories, Nunavut, PEI, Quebec, Saskatchewan, YukonUnited States: Alaska, Hawaii, Iowa, Louisiana, Mississippi, Nebraska, New Mexico, Oklahoma, Rhode Island, South Dakota, West Virginia, WyomingCandidates must reside in an eligible location, which vary by role. How we work Our values guide how we support customers, collaborate with colleagues, develop products, and foster a culture of belonging. They define not just our actions, but what it means to be Dutonian. People Leaders at PagerDuty are responsible for creating high performance environments that drive accountability. PagerDuty has four key dimensions that define our Leadership Impact: Lead Self, Lead the Team, Lead the Business, and Lead the Future. Each dimension has three associated competencies to give leaders a shared language for guiding their development, career, promotion, and succession planning discussions. Our Manager Expectations serve as a practical guide for managers to understand their responsibilities, prioritize their efforts, and drive engagement and performance. What we offer As a global organization, our total rewards approach is competitive with industry standards and aligned with local laws and regulations. Learn more, including country-specific offerings, on our benefits site. Your package may include: Competitive salary Comprehensive benefits package  Flexible work arrangements Company equity* ESPP (Employee Stock Purchase Program)* Retirement or pension plan* Generous paid vacation time Paid holidays and sick leave Dutonian Wellness Days & HibernationDuty - companywide paid days off in addition to PTO Paid parental leave: 22 weeks for pregnant parent, 12 weeks for non-pregnant parent (some countries have longer leave standards and we comply with local laws)* Paid volunteer time off: 20 hours per year Company-wide hack weeks Mental wellness programs *Eligibility may vary by role, region, and tenure About PagerDuty PagerDuty, Inc. (NYSE:PD) is a global leader in digital operations management. The PagerDuty Operations Cloud is an AI-powered platform that empowers business resilience and drives operational efficiency for enterprises. With a generative AI assistant at its core, PagerDuty empowers teams to detect and resolve issues in real time, orchestrate complex workflows, and drive continuous improvement across their digital operations. Trusted by nearly half of both the Fortune 500 and the Forbes AI 50, as well as approximately two-thirds of the Fortune 100, PagerDuty is essential for delivering always-on digital experiences to modern businesses PagerDuty is Great Place to Work-certified™, a Fortune Best Workplace for Millennials, a Fortune Best Medium Workplace, a Fortune Best Workplace in Technology, and a top rated product on TrustRadius and G2.  Go behind-the-scenes on our careers site and @pagerduty on Instagram. Additional Information PagerDuty is an equal opportunity employer. PagerDuty does not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, parental status, veteran status, or disability status. Your privacy is important to us. By submitting an application, you confirm that you have read and understand PagerDuty's Privacy Policy. PagerDuty is committed to providing reasonable accommodations for qualified individuals with disabilities in our job application process. Should you require accommodation, please email accommodation@pagerduty.com and we will work with you to meet your accessibility needs. PagerDuty uses the E-Verify employment verification program. To apply: https://weworkremotely.com/remote-jobs/pagerduty-account-manager-us

Headquarters: United States, Remote Job Title:  Financial Analyst Location: United State, REMOTE Salesloft are building the next era of enterprise revenue — one where teams make confident decisions powered by AI and real signals. By combining our scale, insights, and AI innovation, we’re building the industry’s first Predictive Revenue System, enabling humans and AI to work together to make smarter decisions and drive consistent growth. With thousands of customers using our platforms every day, we have an unmatched view into how revenue is actually won — the Revenue Context that reveals what happens, when, and with what outcome. This gives us a unique opportunity to transform an entire category and set a new benchmark for how modern revenue teams operate. Join us to help transform how companies around the world run revenue — and build the platform that will guide leading revenue teams into the future. THE OPPORTUNITY: At Salesloft, our Financial Analyst will be pivotal to our company’s success. You will be a key member of our fast-growing and high-performing Finance team and will be a critical partner in scaling the company by building key business relationships across the organization. We believe that the most successful SaaS businesses rely on agile, data-driven finance partners who look beyond budget variances to turn operational data into strategic growth. On a day-to-day basis, you will be responsible for serving as the dedicated finance partner to our Customer Success, Professional Services, and G&A organizations alongside our FP&A leadership. Specifically, you will: Lead Financial Partnering: Support departmental heads with headcount management, monthly budgeting, forecasting, and actuals variance analysis. Maintain Revenue & Retention Metrics: Own the source of truth for retention and churn forecasting models, partnering directly with Revenue Operations and Order Management to ensure data integrity. Drive Executive Reporting: Prepare monthly and quarterly management reporting—analyzing financial results, identifying key operational trends, and communicating insights to senior leadership. Leverage Modern Tech & AI: Utilize Pigment as our core FP&A planning platform and Claude AI to accelerate data analysis, reporting, and scenario modeling to automate finance workflows. Execute Strategic Modeling: Perform ad-hoc financial modeling and scenario analyses to evaluate operational risks and strategic business initiatives. In addition to working with amazing colleagues who exemplify our ‘team over self’ core value, you will also have the opportunity to work directly across different management levels to solve complex financial challenges and shape how we scale a world-class revenue platform. You will have an opportunity to make a difference. WHAT WE’RE LOOKING FOR: We are seeking a self-motivated, customer-centric, and highly analytical problem solver who is passionate about making an impact. You are an independent thinker with an eye for process improvement, comfortable navigating fast-paced environments, and eager to leverage cutting-edge tools to automate finance workflows. If you’re looking for an opportunity to learn more, do more, and become more, then becoming a Financial Analyst is the career path for you! THE TEAM: The Finance team consists of results-oriented SaaS professionals with a strong analytical mindset and a passion for strategic problem solving. The team members share a few common traits: they are collaborative, highly curious, detail-oriented, and focused on helping the company scale cleanly. THE SKILL SET: 2 to 3 years of experience in FP&A, Sales Operations, or quantitative financial analysis roles within a high-growth tech or B2B SaaS environment. Advanced proficiency in Microsoft Excel / Google Sheets for financial modeling. Hands-on experience with modern FP&A platforms (specifically Pigment) and comfort using AI tools (such as Claude AI) to drive analytical productivity. Solid understanding of core SaaS post-sales business metrics (e.g., NRR, GRR, Churn, ARR). Strong communication, interpersonal, and presentation skills to interact effectively with business partners and executive management. High adaptability and problem-solving skills; comfortable working in a fast-paced team with evolving priorities. Collaborative mentality by prioritizing ‘we’ and not focusing on ‘me’.  At Salesloft, we are committed to creating an inclusive and supportive workplace where everyone belongs and can thrive. We focus on culture add, not culture fit, and believe our teams are made stronger by the unique perspectives, experiences, and identities each person brings. We are proud to be an Equal Opportunity Employer and provide employment opportunities to all employees and applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, pregnancy, or any other characteristic protected by law. If you’re excited about this role even though your experience may not perfectly match every requirement, we encourage you to apply. We are actively hiring across multiple geographies and would love to welcome passionate, curious, and mission-driven individuals to our growing team. Explore our open roles and consider joining us! ______________________________________________________________________________________________ Please note that all official communication regarding job opportunities at Salesloft will come from @ salesloft.com email address. If you receive messages on LinkedIn or other job platforms claiming to be from Salesloft, they may not be legitimate. To verify the authenticity of any job-related communication, please visit our official Careers site. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, notetaking, or summarizing responses. These tools assist our recruitment team but do not replace human judgment — all hiring decisions are made by people. If you would like more information about how your data is processed or prefer to opt out of any AI-assisted tools, please let your recruiter know. Opting out will not impact your experience or consideration.   #LI-REMOTEIt is Salesloft’s intent to pay all Lofters competitive wages and salaries that are motivational, fair and equitable.  The goal of Salesloft’s compensation program is to be transparent, attract potential employees, meet the needs of all current employees and encourage employees to stay with our organization.   Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to skill set, depth of experience, certifications, and specific work location. The total compensation package for this position may also include performance bonus, benefits and/or other applicable incentive compensation plans. Base Pay Range$67,000—$77,500 USD To apply: https://weworkremotely.com/remote-jobs/salesloft-financial-analyst

Headquarters: Mexico URL: http://lawnstarter.com About LawnStarter LawnStarter is the nation's leading on-demand marketplace for lawn care and related services, with over $150M in annual bookings. We're expanding beyond lawn care to become the one-stop shop for all home services. About Engineering Quality at LawnStarter Our QA team is growing, and we're investing real money in better test coverage. We already have shared quality standards and a QA squad that organizes itself horizontally across teams. What we don't have is someone dedicated to owning that vision: every QA is heads-down on their own team, so nobody has the room to drive the standards forward, unify how the squad works, or push the state of the art. That's the gap this role fills. It's not a nice-to-have we're adding because things are going well. It's the structure and leadership we need to make what we've already built actually compound. The Role You'll be LawnStarter's first Principal Quality Engineer, reporting directly to the Head of Engineering. We already have quality standards, working CI/CD gates, and AI tooling in the mix. Nobody owns the vision behind all of it, drives it forward, or leads the QA squad that keeps it running. You will. This isn't a QA management job today. You won't spend your day approving tickets or chasing bug counts. You'll take ownership of the standards and tooling that already exist, work collaboratively with the QA squad to improve them, and keep pushing the state of quality engineering forward as the org grows. As the QA squad grows, this role could take on direct people management of QAs, so hiring, coaching, and performance management experience is a real plus even though it's not the day-one job. You're not starting from zero, and you're not inheriting a mess either. That means the job isn't "invent a strategy nobody has thought about." It's "listen to the QAs who live in this every day, understand where the pain is, and lead them toward what's next." We need someone who reads where LawnStarter is today and builds from there, not someone who shows up with a favorite tool stack and a coverage number they picked before they met the team. What makes this role different: You own and evolve the quality strategy together with the QA team, instead of building one in a vacuum or just executing someone else's. You have direct sponsorship from the Head of Engineering and the room to keep growing the AI-native tooling already in the mix. Your success is measured by how much better the whole engineering org's quality gets under your leadership, not by a headcount number. What You'll Own Strategy and vision: The company-wide quality engineering roadmap, plus a quality accountability framework that spells out what engineers, EMs, and PMs each own at every stage of building software. Test strategy across the stack: Unit, component, contract, API, end-to-end, mobile, and non-functional testing (performance, load, accessibility), agreed with each team as their quality contract. AI-native quality tooling: AI agents and skills, including Claude Code style tooling, that any engineer can run on demand for test generation, code review, and quality guidance. You'll keep hunting for the next AI capability worth putting in front of the team. CI/CD and test infrastructure: Required checks, quality gates, E2E and visual regression pipelines, performance budgets, and the mobile test automation strategy across emulators and real device clouds. That includes deciding what actually needs to block a deploy versus what can run async, and keeping the pipeline itself fast. Production quality signal: Tying monitoring into incident response and building dashboards teams actually check, not ones that just exist. Technical mentorship of the QA discipline: QA engineers keep reporting to their own Engineering Managers today. You won't manage their day-to-day or their careers right now. You'll own the technical and craft side of QA org-wide, mentor QA engineers across every squad, and send your input to their EMs to feed performance reviews. That could change as the squad grows into a direct reporting line to this role. Problems to Solve A solid quality bar with no one steering it. We already have shared standards, working quality gates, and AI tooling in the mix. What's missing is someone whose job is to look at all of it, decide what needs to improve next, and actually drive that improvement instead of it being everyone's part-time responsibility. A QA squad with no dedicated leadership. Our QAs already organize horizontally across teams, but every one of them is focused on their own team's work day to day. Nobody has the bandwidth to unify how they work, spread what's working on one team to the others, or represent their pain points where decisions get made. You'll give that squad the structure and leadership it's missing. Standards that need continuous R&D, not a rewrite. The foundation works. The risk is standing still while the org grows. You'll keep pushing the state of the art, testing new approaches and tools, and deciding what's worth rolling out broadly versus what stays an experiment. Quality work that's still someone's side project. Right now, improving quality practice competes with each QA's day-to-day team commitments. You'll make it someone's actual job to carry that forward, and get engineers, EMs, and PMs treating it as planned work instead of something squeezed in. What Success Looks Like (Year 1) A clear quality vision, owned and communicated: Every product team can point to what "good" means for their testing and why, with you as the person who set that direction and keeps it current. Measurable improvement on existing gates: Flakiness, pipeline cost, and what runs sync versus async on core repositories are visibly better than when you started, not just maintained. At least one new AI-native capability shipped: You've pushed the existing AI tooling forward with something new, like an added test-generation flow or audit, that engineers actually reach for weekly. A QA squad that feels led: The QAs across teams can point to concrete ways their work, tools, or standards improved because someone was finally driving it. Requirements Who You Are AI-native, specifically for quality work. You already use AI to generate tests, not just to autocomplete code. You've set up agentic tooling like Claude Code or MCP-based workflows so engineers can run on-demand test generation or code review against their own repos, and you keep experimenting with what AI can take off a team's plate next. This is unlikely to be a good fit if AI tools mostly make you nervous, or your use of them stops at your own personal productivity. A strategic thinker, not a tool zealot. Give you a team's current maturity level, and you'll design the testing approach that fits where they are, not the one you used at your last job. You resist the urge to mandate a specific framework or a specific coverage number before you understand the context. Someone who shows up insisting "we need to hit 90% coverage" or "everyone must use Playwright" without first learning how the team works will struggle here. Deeply hands-on across the whole test pyramid. You've built and maintained component, contract, API, E2E, and performance test suites yourself, not just reviewed slides about them. You're the person who steps in when the engineering team is blocked by the pipeline and can't ship. If your test automation experience stops at reading dashboards other people built, this role will feel out of reach fast. A patient teacher who still ships. Coaching engineers on testing practice and running enablement sessions is part of the job. So is personally building the CI pipelines and the tooling. You don't write the doc and hope someone else implements it. This is unlikely to be a good fit for someone who only wants to advise, or who avoids hands-on infrastructure work. Comfortable owning influence without owning headcount, at least for now. You'll mentor QA engineers across every squad on technical craft and send notes to their EMs for performance reviews. You won't be their manager on day one, and you won't set their career path. This works well if you're motivated by discipline-wide technical influence. It won't if you need direct reports from the start to feel engaged. If you've hired, coached, and managed performance for a QA or engineering team before, that's a genuine plus: this role could grow into managing the QA squad directly as it scales. This Role Is NOT A traditional QA management job, at least not on day one: You won't manage QA engineers day to day or own their career growth right now. Their EMs do that. You own the technical and strategic direction of the QA discipline instead, with the door open to direct management as the squad grows. A "throw out what's there and start over" job: We have real standards and tooling worth building on. You can't parachute in with a pre-packaged process or a favorite tool stack and mandate it regardless of fit. A ticket-approval or gatekeeping role: You're not the last line of defense that blocks releases at the end. You're embedding quality earlier, so there's less to block. A headcount-growth play: Your success isn't measured by how big a QA team you build. It's measured by how much better the whole engineering org's quality gets. Benefits Compensation & Benefits Base salary: $80,000-$100,000 USD annually. Fully remote: This is deep-focus analytical work with US-facing partners. We hire the best analyst regardless of city and trust you to manage your environment and overlap hours. Flexible PTO: Measured on outcomes, not hours logged. LawnStarter provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, or genetics. We comply with applicable state and local laws governing nondiscrimination in employment. To apply: https://weworkremotely.com/remote-jobs/lawnstarter-principal-quality-engineer-1

Headquarters: Brazil URL: http://lawnstarter.com About LawnStarter LawnStarter is the nation's leading on-demand marketplace for lawn care and related services, with over $150M in annual bookings. We're expanding beyond lawn care to become the one-stop shop for all home services. About Engineering Quality at LawnStarter Our QA team is growing, and we're investing real money in better test coverage. We already have shared quality standards and a QA squad that organizes itself horizontally across teams. What we don't have is someone dedicated to owning that vision: every QA is heads-down on their own team, so nobody has the room to drive the standards forward, unify how the squad works, or push the state of the art. That's the gap this role fills. It's not a nice-to-have we're adding because things are going well. It's the structure and leadership we need to make what we've already built actually compound. The Role You'll be LawnStarter's first Principal Quality Engineer, reporting directly to the Head of Engineering. We already have quality standards, working CI/CD gates, and AI tooling in the mix. Nobody owns the vision behind all of it, drives it forward, or leads the QA squad that keeps it running. You will. This isn't a QA management job today. You won't spend your day approving tickets or chasing bug counts. You'll take ownership of the standards and tooling that already exist, work collaboratively with the QA squad to improve them, and keep pushing the state of quality engineering forward as the org grows. As the QA squad grows, this role could take on direct people management of QAs, so hiring, coaching, and performance management experience is a real plus even though it's not the day-one job. You're not starting from zero, and you're not inheriting a mess either. That means the job isn't "invent a strategy nobody has thought about." It's "listen to the QAs who live in this every day, understand where the pain is, and lead them toward what's next." We need someone who reads where LawnStarter is today and builds from there, not someone who shows up with a favorite tool stack and a coverage number they picked before they met the team. What makes this role different: You own and evolve the quality strategy together with the QA team, instead of building one in a vacuum or just executing someone else's. You have direct sponsorship from the Head of Engineering and the room to keep growing the AI-native tooling already in the mix. Your success is measured by how much better the whole engineering org's quality gets under your leadership, not by a headcount number. What You'll Own Strategy and vision: The company-wide quality engineering roadmap, plus a quality accountability framework that spells out what engineers, EMs, and PMs each own at every stage of building software. Test strategy across the stack: Unit, component, contract, API, end-to-end, mobile, and non-functional testing (performance, load, accessibility), agreed with each team as their quality contract. AI-native quality tooling: AI agents and skills, including Claude Code style tooling, that any engineer can run on demand for test generation, code review, and quality guidance. You'll keep hunting for the next AI capability worth putting in front of the team. CI/CD and test infrastructure: Required checks, quality gates, E2E and visual regression pipelines, performance budgets, and the mobile test automation strategy across emulators and real device clouds. That includes deciding what actually needs to block a deploy versus what can run async, and keeping the pipeline itself fast. Production quality signal: Tying monitoring into incident response and building dashboards teams actually check, not ones that just exist. Technical mentorship of the QA discipline: QA engineers keep reporting to their own Engineering Managers today. You won't manage their day-to-day or their careers right now. You'll own the technical and craft side of QA org-wide, mentor QA engineers across every squad, and send your input to their EMs to feed performance reviews. That could change as the squad grows into a direct reporting line to this role. Problems to Solve A solid quality bar with no one steering it. We already have shared standards, working quality gates, and AI tooling in the mix. What's missing is someone whose job is to look at all of it, decide what needs to improve next, and actually drive that improvement instead of it being everyone's part-time responsibility. A QA squad with no dedicated leadership. Our QAs already organize horizontally across teams, but every one of them is focused on their own team's work day to day. Nobody has the bandwidth to unify how they work, spread what's working on one team to the others, or represent their pain points where decisions get made. You'll give that squad the structure and leadership it's missing. Standards that need continuous R&D, not a rewrite. The foundation works. The risk is standing still while the org grows. You'll keep pushing the state of the art, testing new approaches and tools, and deciding what's worth rolling out broadly versus what stays an experiment. Quality work that's still someone's side project. Right now, improving quality practice competes with each QA's day-to-day team commitments. You'll make it someone's actual job to carry that forward, and get engineers, EMs, and PMs treating it as planned work instead of something squeezed in. What Success Looks Like (Year 1) A clear quality vision, owned and communicated: Every product team can point to what "good" means for their testing and why, with you as the person who set that direction and keeps it current. Measurable improvement on existing gates: Flakiness, pipeline cost, and what runs sync versus async on core repositories are visibly better than when you started, not just maintained. At least one new AI-native capability shipped: You've pushed the existing AI tooling forward with something new, like an added test-generation flow or audit, that engineers actually reach for weekly. A QA squad that feels led: The QAs across teams can point to concrete ways their work, tools, or standards improved because someone was finally driving it. Requirements Who You Are AI-native, specifically for quality work. You already use AI to generate tests, not just to autocomplete code. You've set up agentic tooling like Claude Code or MCP-based workflows so engineers can run on-demand test generation or code review against their own repos, and you keep experimenting with what AI can take off a team's plate next. This is unlikely to be a good fit if AI tools mostly make you nervous, or your use of them stops at your own personal productivity. A strategic thinker, not a tool zealot. Give you a team's current maturity level, and you'll design the testing approach that fits where they are, not the one you used at your last job. You resist the urge to mandate a specific framework or a specific coverage number before you understand the context. Someone who shows up insisting "we need to hit 90% coverage" or "everyone must use Playwright" without first learning how the team works will struggle here. Deeply hands-on across the whole test pyramid. You've built and maintained component, contract, API, E2E, and performance test suites yourself, not just reviewed slides about them. You're the person who steps in when the engineering team is blocked by the pipeline and can't ship. If your test automation experience stops at reading dashboards other people built, this role will feel out of reach fast. A patient teacher who still ships. Coaching engineers on testing practice and running enablement sessions is part of the job. So is personally building the CI pipelines and the tooling. You don't write the doc and hope someone else implements it. This is unlikely to be a good fit for someone who only wants to advise, or who avoids hands-on infrastructure work. Comfortable owning influence without owning headcount, at least for now. You'll mentor QA engineers across every squad on technical craft and send notes to their EMs for performance reviews. You won't be their manager on day one, and you won't set their career path. This works well if you're motivated by discipline-wide technical influence. It won't if you need direct reports from the start to feel engaged. If you've hired, coached, and managed performance for a QA or engineering team before, that's a genuine plus: this role could grow into managing the QA squad directly as it scales. This Role Is NOT A traditional QA management job, at least not on day one: You won't manage QA engineers day to day or own their career growth right now. Their EMs do that. You own the technical and strategic direction of the QA discipline instead, with the door open to direct management as the squad grows. A "throw out what's there and start over" job: We have real standards and tooling worth building on. You can't parachute in with a pre-packaged process or a favorite tool stack and mandate it regardless of fit. A ticket-approval or gatekeeping role: You're not the last line of defense that blocks releases at the end. You're embedding quality earlier, so there's less to block. A headcount-growth play: Your success isn't measured by how big a QA team you build. It's measured by how much better the whole engineering org's quality gets. Benefits Compensation & Benefits Base salary: $80,000-$100,000 USD annually. Fully remote: This is deep-focus analytical work with US-facing partners. We hire the best analyst regardless of city and trust you to manage your environment and overlap hours. Flexible PTO: Measured on outcomes, not hours logged. LawnStarter provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, or genetics. We comply with applicable state and local laws governing nondiscrimination in employment. To apply: https://weworkremotely.com/remote-jobs/lawnstarter-principal-quality-engineer

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