LangChain/LangGraph

What You ll Do

• Design and implement agent-based workflows using LangGraph
• Build and optimize LangChain pipelines (tools, chains, agents, memory)
• Develop RAG systems with vector databases (FAISS, Pinecone, Weaviate, etc.)
• Integrate LLMs (OpenAI, Anthropic, open-source models) into production services
• Implement tool-calling, function calling, and structured outputs
• Handle prompt engineering, evaluation, and iterative improvement
• Ensure reliability, observability, and cost-efficiency of LLM systems
• Collaborate with product, backend, and ML teams to ship features end-to-end

Required Qualifications

• Strong Python experience (production-level)
• Hands-on experience with LangChain
• Practical experience with LangGraph (stateful agents, branching flows, retries)
• Experience building or deploying LLM-powered applications
• Familiarity with vector databases and embeddings
• Understanding of prompt design, hallucination mitigation, and evaluation
• Experience integrating APIs and external tools into AI workflows

Nice to Have

• Experience with FastAPI or similar backend frameworks
• Experience deploying LLM systems to cloud platforms (AWS, Google Cloud Platform, Azure)
• Familiarity with open-source LLMs (LLaMA, Mistral, etc.)
• Experience with streaming, async pipelines, or background workers
• Knowledge of LLM observability tools (LangSmith, OpenTelemetry, custom logging)
• Prior work on agentic systems or multi-step reasoning tasks