Charter Communications is seeking an AI/ML Engineer for a 6-month contract position based in St. Paul, Minnesota. This role focuses on designing and developing advanced AI systems, including LLM-powered agents, multi-agent orchestration, and retrieval-augmented generation (RAG) pipelines.
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
Qualifications
Required
10+ years of software development with strong Python expertise in production environments
2+ years hands-on LLM development (LangChain, LangGraph, or equivalent frameworks)
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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
Preferred
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
