Senior Python Backend Engineer, Reef Technologies
Company:
Location: Remote
Published: 1970-01-01
Warsaw (fully remote), Poland
Senior Python Backend Engineer
Weâre looking for Python backend engineers to work on a trustless supercluster of performance-proofed GPU-enabled sandboxed docker container runners controlled by truly decentralized algorithms (not just PAXOS or RAFT).
Wow, that was a mouthful...
If you found it interesting, join Reef Technologies and tackle complex technical challenges like this on your own terms:
Contribute from wherever you likeâwe are fully remote but like to stay in sync, so weâre currently hiring in EMEA/APAC.
Set your own time commitment, as long as itâs at least 30h per week
See how we work in our handbook
Influence the way we operate through our Sociocracy 3.0 decision-making process
Salary on a B2B contract:
45-70 USD or 180-280 PLN per hour
Flexible work schedule (as measured with a time tracker)
We automatically adjust rates based on inflation twice a year
So, what do you think? You don't even need a CV, just click here and shoot a few quick commands to apply.
We're looking for someone with 5+ years of programming experience, including at least a year with Python (including opensource and significant personal projects).
GenAI & Python Specialist, Deloitte
Company:
Location: Remote
Published: 1970-01-01
Toronto, Ontario, Canada
Deloitte is seeking an experienced GenAI & Python Specialist to join our dynamic Operate team on a 1âyear fixed term employment basis. In this role, you will design, build, and scale Generative AI solutions using Pythonâbased frameworks, Large Language Models (LLMs), and advanced retrievalâaugmented generation (RAG) techniques.
What will your typical day look like?
-Strong Python development for GenAI and agentic systems
Design and implementation of Agentic AI workflows using LangChain, LangGraph, ADK, MCP
Development and orchestration of multiâagent systems
Implementation of RetrievalâAugmented Generation (RAG), including advanced RAG techniques
Integration and management of vector databases for RAG workflows
Design and implementation of memory systems (shortâterm, longâterm, persistence, conversational checkpoints)
Agentic AI design and orchestration across workflows
Work with AI/GenAI models including Gemini and Claude 4.5 on Vertex AI
Development of business coâpilots, including coâpilot solutions for Risk Analysts
Support for business process optimization using GenAI
Use of NLU as an addâon capability where requiredContribution to CTOâled tools, including:
Agent Flow for observability, drift monitoring, feedback loops
ML Flow for model evaluation and drift detection
Sourcing test results management, including truth tables and evaluations
Bringing Agent Flow into existing projects
Domainâspecific GenAI solutions for DRO (Data and Regulatory Operations):
QA validation and KYC document processing
Systematic capture and validation of required fields
Automated document checking without extraction
Record retrieval and comparison (DNC, ANC, SMC)
Agentic framework for document management, data analysis, and data engineering
CoâLabs initiatives:
Consolidation across MCP endpoints
Agent registries consolidation
Combining assets into an accessible catalog
Pythonâbased web scraping and utility development
Work with existing Python GitHub repositories
Integration with case management tools and Appian workflows (NA10)
Building agents on top of Appian workflows using ADK
You are someone with these skills, experience & qualifications:
6+ years of handsâon experience designing and implementing AI / GenAI solutions using Python
Strong proficiency in Python engineering for data processing, model integration, APIs, and microservices
Deep understanding of Generative AI, LLMs, and NLP concepts and architectures
Experience building agentic AI workflows using LangGraph, including multiâstep reasoning, toolâcalling, and plannerâexecutor patterns
Advanced knowledge of RAG techniques, including hybrid search, vector and multiâvector retrieval, embeddings, and context optimization
Experience designing and deploying APIs and microservices to production environments
Familiarity with traditional ML/NLP techniques such as clustering, extraction, and enrichment to complement GenAI solutions
Strong communication skills, a collaborative mindset, and a passion for continuous learning and innovation in the GenAI space