Staff Fullstack Engineer, Agentic Applications
Technical lead building production agentic/LLM systems to automate HR, recruiting, and People Tech workflows at Databricks. Requires 8+ years engineering experience and 2+ years with agents, RAG, and multi-agent orchestration.
About the job
What you'll do
- Architect and build agentic systems that automate and augment People Tech workflows — onboarding, offboarding, comp analysis, policy Q&A, HR service delivery — using LLM orchestration frameworks (LangGraph, AutoGen, or equivalent).
- 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.
- Integrate People Tech systems (Workday, Greenhouse, ADP etc.) as agent-accessible tools and data sources via Databricks Unity Catalog and MCP-style interfaces.
- Set the technical bar for the pod — reviewing designs, establishing engineering standards, and leading architectural reviews across the People Tech roadmap.
- 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.
What we're looking for
- 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).
- Deep fluency in Python and experience with agentic frameworks — LangChain/LangGraph, CrewAI, AutoGen, Semantic Kernel, or similar.
- Strong command of enterprise integration patterns: REST/GraphQL APIs, event-driven architecture, and connecting SaaS HR/HCM platforms programmatically.
- Experience with data platforms — Databricks, Spark, or equivalent — and building AI applications on top of lakehouse or warehouse architectures.
- Track record as a technical lead: driving architectural decisions, writing RFCs, and raising the quality bar across a team without relying on management authority.
Nice to have
- Prior experience in People Tech, HR tech, or internal tooling domains.
- Familiarity with Workday, Greenhouse or similar enterprise HR platforms — especially via API or integration layer.
- Experience evaluating and red-teaming LLM agents for safety, reliability, and correctness in sensitive business contexts.
Skills
Python, LangChain, LangGraph, Crewai, Autogen, Semantic Kernel, REST APIs, GraphQL, Databricks, Spark, RAG, Llm Orchestration
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