Description

Design and deploy production-grade agentic systems using LangGraph, managing complex node logic, branching, and memory. You will build, optimize, and maintain scalable LLM orchestration pipelines that interact with external APIs, databases, and models.

This role is hybrid.

Responsibilities

• Design and implement advanced LangGraph workflows with complex node logic, branching, and stateful memory management.
• Lead the development of agentic systems that reason, adapt, and interact dynamically with external environments.
• Optimize performance, scalability, and fault tolerance of LangGraph graphs in production environments.
• Integrate LangGraph with external APIs, databases, and LLMs (OpenAI, Anthropic) to create seamless intelligent pipelines.
• Mentor junior developers, establish best practices, and collaborate with AI researchers to translate ideas into robust implementations.

Required Skills

• 10+ years of software engineering experience, including 2+ years with LangGraph or agentic frameworks.
• Expert-level proficiency in Python, asynchronous programming, and graph-based computation.
• Deep understanding of LLM orchestration, prompt engineering, and stateful agent design.
• Hands-on experience with LangChain, OpenAI, Anthropic, or similar LLM platforms.
• Strong grasp of workflow debugging, graph visualization, and LangGraph Studio.
• Proficiency in CI/CD processes and monitoring for AI/LLM applications.
• Experience with RAG, batch processing, and evaluation metrics for agentic systems.
• Ability to build production-grade agentic systems with high reliability.

Preferred Skills

• Experience with AgenticAI model design and deployment at production level.
• Background in AI research or product teams translating abstract concepts into engineering solutions.

Key Skills

Education

Any Graduate