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 Postgre

SQL, SSM, IAM, EKS

)

Telecommunications or field service domain experience

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