W2 Role : AI/ML Developer

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