Staff Fullstack Engineer, Agentic Applications

• 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.

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

Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above.

Local Pay Range $192,000-$260,000 USD, At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees.

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., Databricks is the data and AI company. More than 10,000 organizations worldwide - including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 - rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark , Delta Lake and MLflow. To learn more, follow Databricks on Twitter, LinkedIn and Facebook.