Role Summary
We are looking for a skilled AI/ML Developer to join our agentic platform team on a contractual basis. 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 of 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
TechMobile Agentic AI Platform | Charter Communications
Tech Stack
Category Technologies
Language Python 3.11+
Frameworks: FastAPI, LangChain, LangGraph
LLM APIs Azure OpenAI (GPT-4)
Databases: PostgreSQL (Aurora), OpenSearch (vector)
Messaging: WebSocket, SSE, REST
Observability: Langfuse, Datadog, Splunk
Infrastructure: Docker, Kubernetes (EKS), AWS
CI/CD GitLab CI, Helm, ArgoCD
Package Mgmt: uv (Python), pyproject.toml
Testing pytest, unittest, FastAPI TestClient
TechMobile Agentic AI Platform | Charter Communications
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
- Dice Id: RTL155990
- Position Id: 85ecd7ab4bb83e668195ec42df2127f3
- Posted 12 hours ago
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