Responsibilities
- Design, implement, and own multi-step agentic flows using LangChain, LangGraph, and similar.
- Build tools, agents, and chains that connect to live data sources (APIs, databases, time-series feeds)
- Integrate LLMs (Claude, GPT, Gemini, etc') into reliable, observable pipelines
- Own prompt engineering, context management, and output validation
- Experience working in large-scale and big data environments
- Deploy and monitor AI services on AWS or Azure
- Instrument flows with logging and tracing so we can debug and improve them
- Build React interfaces that surface AI outputs: summaries, alerts, recommendations, and interactive co-pilot features
- Connect frontend components to streaming AI responses
- Write clean, maintainable TypeScript code
Requirements
- 6+ years of full-stack development experience
- Hands-on, production-grade experience with LangChain and LangGraph or similar agentic orchestration in production, not just tutorials
- Strong Python for AI/backend work and TypeScript/React for frontend
- Experience integrating LLMs via API (Bedrock, GCP Agent Platform, or similar)
- Familiarity with vector stores, RAG pipelines, and structured output parsing
- Comfort working in a fast-moving startup environment where you own your features end-to-end
Nice to Have
- Experience in energy, IoT, or industrial data domains
- Experience with data pipelines such as Lambda/Medallion with data integrity validations
- Familiarity with LangFuse or other LLM observability tools
- Experience with MongoDB Atlas, ClickHouse, and time-series data
Work Arrangement
Remote (Worldwide)
