Senior AI/ML Engineer

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