Role:-Senior AI/ML Engineer
Location: St. Louis, MO (Locals only)
Duration:- Long term
We are looking for a skilled AI/ML Developer to join our agentic platform team. You will design, develop, and deploy LLM-powered agents and pipelines that directly serve field technicians in production. You will work closely with the platform architect and contribute to the core multi-agent orchestration system.
Key Responsibilities
- Design and develop LLM-powered agents using LangGraph and LangChain frameworks
- Build and enhance multi-agent orchestration pipelines with conditional routing, state management, and error recovery
- Develop RAG pipelines with hybrid search (semantic + keyword), re-ranking, and Reciprocal Rank Fusion
- Implement tool-calling agents with parallel API execution, sequential enrichment chains, and summarization
- Build real-time streaming capabilities (WebSocket / SSE) for conversational AI
- Integrate with Azure OpenAI APIs with circuit breaker patterns and fallback chains
- Implement prompt engineering and dynamic prompt management (DB-backed with in-memory caching)
- Design and implement multi-modal AI features (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
Required Skills & Experience
Must-Have
- 10+ years of software development with strong Python expertise in production environments
- 2+ years hands-on LLM development (LangChain, LangGraph, or equivalent frameworks)
- RAG pipeline experience - embeddings, vector search, re-ranking, answer generation
- LLM APIs - OpenAI Chat Completions, Responses API, streaming, tool calling
- Async Python - asyncio, httpx, FastAPI
- Prompt engineering - system prompts, few-shot, structured JSON output
- Circuit breaker patterns, retry logic, resilient service design
- PostgreSQL and async ORMs (SQLAlchemy async / Alembic)
- Git, CI/CD, Docker, Kubernetes basics
- Strong system design skills - microservices, distributed systems, API design
Nice-to-Have
- LangGraph StateGraph (conditional edges, node pipelines, compiled graphs)
- Multi-agent systems - orchestration, routing, RBAC-based access control
- Langfuse or similar LLM observability (tracing, token usage, latency)
- WebSocket and SSE streaming protocols
- Multi-modal AI (vision models, image analysis)
- Vector databases (OpenSearch, Pinecone, pgvector)
- AWS services (Aurora PostgreSQL, SSM, IAM, EKS)
- Telecommunications or field service domain experience
