Staff Fullstack Engineer, Agentic Applications

<p>P-1477</p> <p>Databricks is transforming how it builds and operates People Technology — moving from traditional SaaS configuration toward an AI-native, agentic stack. You'll be the technical anchor of the People Tech pod, driving the architectural shift from workflow automation to autonomous, multi-agent systems that power HR, recruiting, workforce analytics, and employee experience at scale. This is a rare opportunity to reimagine a critical enterprise domain from the ground up using the very data and AI platform Databricks sells to the world.</p> <p><strong>What you'll do</strong></p> <ul> <li>Architect and build agentic systems that automate and augment People Tech workflows — onboarding, offboarding, comp analysis, policy Q&amp;A, HR service delivery — using LLM orchestration frameworks (LangGraph, AutoGen, or equivalent).</li> <li>Define the agentic platform strategy for the pod: agent design patterns, tool-calling conventions, retrieval-augmented pipelines, evaluation frameworks, and human-in-the-loop guardrails.</li> <li>Integrate People Tech systems (Workday, Greenhouse, ADP etc.) as agent-accessible tools and data sources via Databricks Unity Catalog and MCP-style interfaces.</li> <li>Set the technical bar for the pod — reviewing designs, establishing engineering standards, and leading architectural reviews across the People Tech roadmap.</li> <li>Influence peers and stakeholders: translate agentic capability into business outcomes for People, Legal, and Finance partners, and mentor engineers in the pod on AI-first thinking.</li> </ul> <p><strong>What we're looking for</strong></p> <ul> <li>8+ years of software engineering experience, with at least 2 years building production LLM or agentic applications (agents, RAG pipelines, tool-use, multi-agent orchestration).</li> <li>Deep fluency in Python and experience with agentic frameworks — LangChain/LangGraph, CrewAI, AutoGen, Semantic Kernel, or similar.</li> <li>Strong command of enterprise integration pat