AI Agentic Systems Engineer (LangChain / LangGraph / Google APIs)- F2F

A job description for a role involving LangChain, LangGraph, and Google APIs typically involves creating advanced AI agents and systems. This position, often titled AI/ML Engineer or Agentic Systems Developer, includes designing and implementing complex workflows that use large language models (LLMs) like Google's Gemini and integrate with external tools via Google APIs.

Summary:
This position focuses on developing, deploying, and maintaining advanced AI agents and multi-agent systems. The requirements include experience with LangChain, especially LangGraph for orchestrating stateful agents, and integrating with Google's generative AI models and other cloud APIs

Design and build robust agentic systems for complex tasks and interactions.

Use the LangChain framework to integrate LLMs, tools, and memory.

Use LangGraph to model and orchestrate agents as stateful graphs.

Integrate Google's Generative AI models (e.g., Gemini) using relevant LangChain packages.

Implement tool-calling features for agents to interact with external Google APIs (e.g., Search, Calendar, Cloud services).

Develop and maintain prototypes and production-ready systems.

Collaborate with cross-functional teams.

Apply best practices in AI system development, including monitoring and observability using tools like LangSmith.

Experience in AI/ML engineering, with a focus on agentic AI or autonomous systems development.

Proficiency in Python and the LangChain ecosystem, including LangGraph.

Experience with Google Generative AI models (Gemini) and the langchain-google-genai package.

Experience using Google APIs (e.g., Google Search API, Google Calendar API) for custom tools.