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# Staff Fullstack Engineer, Agentic Applications

- **Company:** Databricks
- **Location:** Mountain View, CA, United States
- **Experience:** Experienced
- **Salary:** $192,000.0 - $260,000.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Software as a Service, Software Design Patterns, Python (Programming Language), Software Engineering, Automated Data Processing (ADP), Large Language Models, Multi-Agent Systems, Apache Spark, Event Driven Architecture, Graphql, Data Management, Workday, Databricks
- **Published:** June 19, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=6d4212f4b0b5ac81

## About the Role

Do you have experience in Technical writing within technology?, * 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.

Pay Range Transparency

## Description

* 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.


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