Senior Python AI/ML Engineer
About The Position
The Senior Python AI/ML Engineer will join a contractual agentic platform team to design, develop, and deploy LLM-powered agents and pipelines that serve field technicians in production. The role works closely with the platform architect and contributes to the core multi-agent orchestration system. The position involves building agent and retrieval-augmented generation capabilities, integrating with Azure OpenAI, supporting real-time conversational AI, and delivering production-quality Python software. The engineer will also participate in code reviews, architecture discussions, and sprint delivery. The contract duration is six months, and interviews are conducted in person.
Requirements
- At least 10 years of software development experience with strong Python expertise in production environments.
- At least 2 years of hands-on LLM development using LangChain, LangGraph, or equivalent frameworks.
- Experience with RAG pipelines, including embeddings, vector search, re-ranking, and answer generation.
- Experience with LLM APIs, including OpenAI Chat Completions, Responses API, streaming, and tool calling.
- Async Python experience with asyncio, httpx, and FastAPI.
- Prompt engineering experience, including system prompts, few-shot prompting, and structured JSON output.
- Experience with circuit breaker patterns, retry logic, and resilient service design.
- Experience with PostgreSQL and async ORMs such as SQLAlchemy async or Alembic.
- Experience with Git, CI/CD, Docker, and Kubernetes basics.
- Strong system design skills, including microservices, distributed systems, and API design.
Nice To Haves
- Experience with LangGraph StateGraph, including conditional edges, node pipelines, and compiled graphs.
- Experience with multi-agent systems, including orchestration, routing, and RBAC-based access control.
- Experience with Langfuse or similar LLM observability tools for tracing, token usage, and latency.
- Experience with WebSocket and SSE streaming protocols.
- Experience with multimodal AI, vision models, or image analysis.
- Experience with vector databases such as OpenSearch, Pinecone, or pgvector.
- Experience with AWS services such as Aurora PostgreSQL, SSM, IAM, or EKS.
- Telecommunications or field service domain experience.
Responsibilities
- Design and develop LLM-powered agents using LangGraph and LangChain.
- Build and enhance multi-agent orchestration pipelines with conditional routing, state management, and error recovery.
- Develop RAG pipelines with hybrid semantic and keyword search, re-ranking, and Reciprocal Rank Fusion.
- Implement tool-calling agents with parallel API execution, sequential enrichment chains, and summarization.
- Build real-time streaming capabilities using WebSocket or SSE for conversational AI.
- Integrate with Azure OpenAI APIs using circuit breaker patterns and fallback chains.
- Implement prompt engineering and dynamic prompt management with database-backed storage and in-memory caching.
- Design and implement multimodal AI features, including image analysis with vision models.
- Write production-quality Python code with error handling, logging, observability, and unit tests.
- Participate in code reviews, architecture discussions, and sprint delivery.
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What This Job Offers
Career Level
Senior
Education Level
No Education Listed
