Engineering Manager, Foundation Model Inference (FMAPI)
Databricks
Engineering Manager, Foundation Model Inference (FMAPI) at Databricks is a full time role based in San Francisco, California, United States. The listing states pay of $190k–$261k. It was published on 22 July 2026 and was open at last check.
| Role | Engineering Manager, Foundation Model Inference (FMAPI) |
|---|---|
| Company | Databricks |
| Location | San Francisco, California, United States |
| Employment type | Full Time |
| Pay (as listed) | $190k–$261k |
| Published | 22 July 2026 |
| Status | Open at last check |
Engineering Manager, Foundation Model Inference (FMAPI)
RDQ427R519
At Databricks, we are driven by a passion to empower data teams in tackling the world's most challenging problems — from revolutionizing transportation to accelerating medical innovations. Our mission is to build and operate the premier data and AI infrastructure platform, enabling our customers to leverage deep data insights for transformative business improvements. If you are passionate about advancing data and AI technologies and are eager to lead a cutting-edge product to success, we invite you to join our dynamic team at Databricks.
The Foundation Model Inference team is the backbone of Databricks’ generative AI capabilities. We build the infrastructure that enables our customers to serve, scale, and optimize frontier models with enterprise-grade reliability and performance. Our Foundation Model APIs provide a unified platform that gives customers access to LLMs with the governance, flexibility, and scalability required for enterprise production workloads.
Databricks is looking for an Engineering leader to lead part of our Foundation Model Inference organization. We are seeking a leader who can build strong teams, uphold a high technical bar, and drive execution on large multi-quarter initiatives in a fast-moving AI infrastructure environment.
The impact you will have
- Lead and grow a team of talented, product-minded infrastructure Engineers working on Databricks Foundation Model Inference and Foundation Model API; The teams owns the systems powering large-scale inference workloads for customers through partner models (OpenAI, Anthropic, Gemini) and self-hosted models (Qwen, GPT-OSS, Llama).
- Help shape the roadmap for products spanning real-time inference, provisioned throughput, and batch inference use cases.
- Partner closely with product and engineering leadership to deliver the right capabilities with strong reliability, quality, and service health.
- Build an inclusive, high-performing team that attracts, develops, and retains exceptional engineers.
- Maintain a deep understanding of your team’s technical area and uphold a strong bar for architecture, implementation quality, and operational excellence.
What we look for
- Experience managing and growing high-performing software engineering teams.
- Strong technical judgment in distributed systems, platform infrastructure, AI/ML infrastructure, or large-scale backend services, with the ability to maintain quality even in areas you have not worked on personally.
- A track record of delivering complex, multi-quarter engineering initiatives with high quality and predictable execution.
- Experience partnering effectively with product management and peer engineering teams to translate customer and business needs into roadmaps and shipped outcomes.
- Operational rigor, including experience with service health, incident response, postmortems, and continuous improvement.
- Excellent communication, coaching, and hiring skills.
- BS in Computer Science or related field.
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
$190,000 — $261,250 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 click here.
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.
Create your free OnJob profile to apply — we'll take you to Databricks's application after sign-up. · Posted 22 Jul 2026.
Engineering Manager, Foundation Model Inference (FMAPI) at Databricks — questions answered
What does the Engineering Manager, Foundation Model Inference (FMAPI) role at Databricks pay?
The Engineering Manager, Foundation Model Inference (FMAPI) at Databricks listing states pay of $190k–$261k for the San Francisco, California, United States position. That figure is taken directly from the employer's own posting as published, not estimated or averaged from other roles.
Where is the Engineering Manager, Foundation Model Inference (FMAPI) role at Databricks based?
Databricks lists this Engineering Manager, Foundation Model Inference (FMAPI) role in San Francisco, California, United States, advertised as full time work at that location. Larger employers sometimes cover several sites under one city name, so confirm the exact office with Databricks before you apply.
Is the Engineering Manager, Foundation Model Inference (FMAPI) role at Databricks still open?
The Engineering Manager, Foundation Model Inference (FMAPI) posting at Databricks was open at OnJob's last check of the employer's careers page, having been published on 22 July 2026. OnJob re-checks source listings on each build and marks a role closed once it disappears, but listings can close without notice, so the employer's own page is the final word.
How do you apply for the Engineering Manager, Foundation Model Inference (FMAPI) role at Databricks?
Apply to the Engineering Manager, Foundation Model Inference (FMAPI) at Databricks role through OnJob with a free profile: OnJob scores your fit against the listing, shows the skills lowering that score, and submits an ATS-ready profile to Databricks's own application page. Creating a profile is free and needs no card.
Related Engineering jobs
Hand-picked roles that match this listing on skills, category and location — each scored to your profile inside OnJob.
Explore more on OnJob
Hiring for a role like this?
Post a job on OnJob and reach AI-matched candidates.