Sr. Developer Advocate, Databricks AI Agentic Systems

at Databricks

San Francisco, United States

RDQ426R238

Location: San Francisco, Bellevue, Amsterdam

Role Overview: Are you a recognized technical leader in Generative AI and MLOps, driven to define the future of production AI Agentic Systems? This Senior Developer Advocate role is a high-level position that grants strategic ownership over developer adoption and technical discourse surrounding Agent Bricks on the Databricks Data Intelligence Platform.

As a crucial link between our engineering teams and the global developer community, you will accelerate the careers of data scientists and AI engineers by coalescing advanced research, customer learnings, and best practices into scalable, production-ready reference implementations, presentations, and demos. You will be instrumental in cultivating the global community for AI Agentic workflows, LLMOps, with particular focus on MLflow, and Agentic System governance.

More About The DevRel Team
At Databricks, we are passionate about enabling data and AI teams to solve the world’s most challenging problems. Our mission in Developer Relations (DevRel) is to empower data practitioners, data scientists, and the broader developer ecosystem by cultivating vibrant communities, crafting exceptional content, and fostering a truly reciprocal relationship with our users. Our primary goal is to drive awareness and adoption of the Databricks Data Intelligence Platform.

The Impact You Will Have
You will leverage your technical depth, community-building skills, and market knowledge to drive awareness and adoption, positioning Databricks as the definitive technical leader in enterprise AI governance and Agentic Systems.

Strategic Roadmap Ownership: Define and execute the global technical advocacy strategy and roadmap for a critical pillar of Databricks AI Agentic Systems (e.g., RAG Architectures, AI Agent Evaluation, or LLM Governance), ensuring alignment with product goals and quantifiable metrics.
Evangelism: Work with the field AI engineers to design and deploy production-grade reference implementations and create high-impact live demonstrations (demos) that solve real-world enterprise GenAI challenges, showcasing best practices in performance, evaluation, and security. You will evangelize Agent Bricks as the definitive way to "Take your AI to your Data".
Technical Content Scaling: Create high-quality, actionable educational resources, including comprehensive courseware, advanced tutorials, technical blog posts, and video content. This content will focus on accelerating the end-to-end AI Agentic workflows and LLMOps lifecycle, including vectorization, prompt engineering, and the use of MLflow, Agent Evaluation, and Agent Feedback for continuous refinement.
Product Influence and Advocacy: Serve as the primary internal technical advocate for the global AI/ML community, translating complex friction points in the developer experience into actionable engineering specifications and influencing the product direction of Agentic Systems.
Community Governance and Growth: Speak and build community by expanding and governing the MLOps and LLMOps communities (including MLflow meetups), mentoring new contributors, and enabling data teams to leverage tools for building MLOps/LLMOps infrastructure. You will establish thought leadership by articulating complex concepts, such as AI Guardrails, lineage tracking, and security controls, within RAG applications, ensuring that Agents are built on governed data.

What We Look For
We are seeking a seasoned Developer Advocate who possesses deep technical proficiency, a verifiable track record of community leadership, and genuine empathy for the developer journey.

Experience and Tenure: 5+ years of total technical experience, including a minimum of 3 years in a dedicated Developer Advocate, Developer Evangelist, Solution Architect, Data Scientist, or AI Field Engineering role.
Production Agentic Systems Track Record: A proven history of building, deploying, and operating production-grade AI Agentic Systems. Expertise in designing robust AI system interactions, implementing RAG chains, and developing autonomous agent applications using the Agent Bricks workflow.
Deep Technical Proficiency: Expert-level knowledge of Python, major machine learning frameworks (e.g., PyTorch, scikit-learn), and modern LLMOps orchestration tools (e.g., LangChain, LlamaIndex, DSPy). Proficient in using MLflow for MLOps; proficiency with Agent Eval and Agent Feedback preferred
Databricks Ecosystem Mastery: Comprehensive understanding of the Databricks Intelligence Platform, particularly MLflow and Agent Bricks. Experience with Model Serving (DS/LLM), training models on the platform, and implementing data governance (Unity Catalog) to ensure Agents operate on governed data is essential.
Verifiable Portfolio and Community Leadership: A demonstrable, high-impact public technical portfolio (e.g., keynote presentations at tier-1 conferences, influential technical articles, significant open source contributions in the AI/ML space, or a successful technical YouTube/podcast series).
Exceptional Communication and Empathy: Exceptional communication skills with a proven talent for translating complex technical concepts into clear, concise educational material for a broad developer audience. Demonstrated ability to mentor junior technical professionals and strategically create scalable programs (e.g., contributor or ambassador initiatives) that foster community engagement and loyalty.

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. For more information regarding which range your location is in visit our page here.

Zone 1 Pay Range

$139,900—$195,850 USD

About Databricks

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.

Benefits

At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region, please visit https://www.mybenefitsnow.com/databricks.

Our Commitment to Diversity and Inclusion

At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics.

Compliance

If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.