Databricks is seeking a Staff Product Manager to lead the strategy, roadmap, and execution for the Agentic AI Applications Platform. This role collaborates across engineering, CIO, and domain teams to deliver enterprise-grade, production-ready agentic applications.
Location and Compensation
Location: Mountain View, CA (onsite)
Salary: USD 172,200 - 236,850 per year
Responsibilities
- Lead the Agentic Platform strategy and roadmap, translating organizational goals into tangible platform capabilities with measurable success criteria and determining release order.
- Define and drive the agent and runtime, establishing a managed agent runtime that supports multi-step orchestration with durable execution, a provider-agnostic model gateway, governed tool invocation, and per-agent guardrails such as cost ceilings, timeouts, and blast radius limits.
- Shape the MCP connector ecosystem by crafting a standardized, bidirectional connectors strategy for various systems of record, including identity propagation, idempotency, dry-run/preview modes, and a connector SDK enabling domain teams to onboard new systems with minimal platform changes.
- Establish the intelligence layer by defining a three-tier data architecture (knowledge graph, context graph, and temporal memory) to enable unified retrieval across vector, structured, and graph sources with source traceability for every context element.
- Develop the evaluation and quality framework, owning the AI-judge pipeline with offline evaluation against golden datasets, online scoring by LLMs, domain-specific judges, and mandatory CI/CD gates to ensure production-ready quality and safety.
- Design a developer-centric experience that enables self-service platform usage. Domain teams should provision agent projects, promote across environments, and access connectors without platform-team tickets, supported by SDKs, CLIs, sandbox environments, templates, and comprehensive documentation, with a target of moving ideas to production in under four weeks for standard agents.
- Define the federation and adoption model across three tiers of usage—platform-built, domain-built on platform, and citizen-developer edge apps—establishing governance gates and a gold-standard promotion pipeline from prototype to hardened service.
Requirements
- 8+ years of product management experience, including at least 3 years on internal platform, infrastructure, or developer-experience products.
- Deep experience in building platforms that other teams rely on, with clear opinions on API design, developer ergonomics, and self-service capabilities.
- Demonstrated experience with AI/ML platforms, agent frameworks, LLM-powered applications, or agentic systems, with understanding of agent runtimes, retrieval augmented generation, and the importance of evaluation.
- Strong technical foundation with the ability to read architecture diagrams, discuss trade-offs with engineers, and make informed prioritization decisions on deeply technical work.
- Experience defining and shipping developer experiences, including SDKs, CLIs, templates, documentation, and self-service workflows; success measured by adoption and developer NPS, not feature count.
- Proven ability to lead cross-functional initiatives across 4+ teams without direct authority, using clarity, conviction, and stakeholder alignment.
- Strong written communication skills for strategy documents, PRDs, and executive briefs that align with VP and CIO audiences.
- Comfort with ambiguity, capable of defining roadmaps for capabilities that do not yet exist in a rapidly evolving space.
Nice to Have
- Experience with Databricks technologies, Lakehouse architecture, Unity Catalog, MLflow, or Delta Lake.
- Familiarity with LangGraph, LangChain, or similar agent orchestration frameworks.
- Knowledge of MCP, A2A, or AG-UI protocols.
- Experience building AI evaluation frameworks such as LLM-as-judge, red-teaming, or automated quality scoring.
- Experience with design systems, component libraries, or frontend platform work.
- Background in enterprise SaaS platform consolidation or migration.
Technologies
LangGraph, LangChain, Model Context Protocol (MCP), A2A protocol, AG-UI protocol, Unity Catalog, MLflow, Delta Lake, Lakehouse architecture, SDK, CLI
About Databricks
Databricks is a data and AI company serving more than 10,000 organizations worldwide. Its Data Intelligence Platform helps enterprises unify data, analytics, and AI. The company is headquartered in San Francisco, with offices globally and a heritage rooted in Lakehouse, Apache Spark, Delta Lake, and MLflow.
Diversity and Inclusion
Databricks is committed to fostering a diverse and inclusive culture and to equitable hiring practices. Hiring is conducted without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical or mental ability, political affiliation, race, religion, or sexual orientation.
Compliance
Access to export-controlled technology or source code may require a U.S. government license. Databricks reserves the right to determine eligibility for such positions and may decline to proceed with an applicant on this basis.
