Senior Software Engineer, Agentic Applications (Full Stack)

Databricks is a data and AI platform that lets organizations build analytics, AI agents, and applications on a unified, governed lakehouse.

Series F+0 current maintainers0 active leads
160 Spear Street, Suite 1300, San Francisco, CA 94105, United States
About Databricks

Data engineers, analysts, and AI teams use Databricks to process large datasets, build reliable pipelines, and train models on a single governed platform. Users can run SQL analytics, serve ML predictions in real time, and deploy AI agents grounded in enterprise data. Its open lakehouse architecture provides consistent security and governance across analytical and operational workloads.

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Skills

Candidate Availability

Required and preferred rules are kept separate and reflect the wording in the original posting.

About the Role

You will design, build, and deploy AI agents for business-critical workflows, building a high-performance React frontend, implementing agentic logic in Python with frameworks like LangChain or LangGraph, integrating backend APIs, and ensuring observability and production readiness.

Requirements

  • 5+ years of full-stack development with strong Python and React.js
  • At least 1 production-deployed AI agent or LLM application
  • Expertise in LLM orchestration, prompt engineering, and tools/plugins
  • Experience with LangChain or LangGraph and ReAct loop
  • Experience with observability, logging, and tracing for AI agents
  • Experience building large-scale enterprise applications
  • Strong API integration experience (REST/GraphQL)
  • Experience in Agile/Scrum environments
  • Strong problem-solving and system design skills

Responsibilities

  • Design, develop, and deploy AI agents for business-critical workflows
  • Implement agentic behaviours with LangChain or LangGraph including ReAct loops
  • Design and develop a high-performance React application for the agent UI
  • Integrate APIs and services and build tools for agents
  • Work with Python/Node.js middleware to orchestrate agent calls and data flow
  • Implement observability and tracing for agent runs
  • Build reusable, scalable UI components
  • Optimise application performance and scalability
  • Participate in architectural discussions
  • Write clean, testable, documented code