RDQ427R534
At Databricks, we are passionate about enabling data teams to solve the world’s toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world’s best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer obsessed — we leap at every opportunity to tackle technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started.
About the RoleWe're looking for a Partner Engineer to lead the technical relationship between Databricks and our strategic AI partnerships - including Anthropic, OpenAI and Google Gemini. You'll own the joint roadmap with their product teams, drive the development of integrations that connect and extend both platforms, and get hands-on with new product features and tooling. You'll collaborate with partners to build POCs that become new products, demos, and hands-on labs - and ultimately the architectures our customers deploy. With direct visibility and engagement with our founders and executives, this high impact role sits in Partner Engineering and works closely with Product, Engineering, Strategic Partnerships and Global GTM teams.
Impact you will have- Serve as the primary technical point of contact across the AI labs, building relationships with senior product and engineering stakeholders to drive joint innovation.
- Work alongside our technical executives to shape the joint product roadmap by translating partner capabilities and integration needs into Databricks platform requirements
- Navigate complex relationships in order to align on joint product offerings that address the needs of Databricks, our partner organizations, and our customers.
- Design and build the integrations that connect and extend both platforms, serving as the hands-on technical expert and early validator of new capabilities.
- Build POCs and reference architectures that hand off cleanly to engineering teams to productize, or to customers to deploy.
- Work with our most strategic customers to align their AI architecture and roadmap needs with what Databricks and our partners are building.
- Develop and maintain technical field enablement content to equip internal & external field teams with the knowledge and tools to deliver joint architectures and articulate differentiated 'better together' value propositions.
- 10+ years in field engineering, consulting, platform architecture, or AI systems development, with the ability to master new technologies quickly while managing multiple partners.
- Depth in how AI systems are built and run in production, across model serving, inference, retrieval, and agent frameworks, and an understanding of how AI products are developed, delivered, and adopted.
- Hands-on engineering skills, with the ability to develop POCs, build demos, and debug integrations that hold up in front of partner engineering teams and customers. Experience with Python and REST APIs and SDKs.
- Established existing relationships within the product and engineering functions of major AI labs and cloud providers.
- Experience in strategic technical partnerships, navigating multi-company engineering initiatives, building consensus across organizations, and leading architectural discussions with clarity.
- Deep knowledge of the Databricks platform and the ability to design AI architectures that span it and a partner's products.
- Communication and influence skills, with the ability to present to engineering teams and executives, and to translate between Product, Engineering, and partner teams.
- Availability to travel globally to partner sites, conferences, and events as required.
- Prior experience in Partner Solutions Architect, Solutions Engineering, or Alliance Engineering roles at AI companies, cloud providers, global system integrators, or major enterprise software companies, with a track record of driving product-to-product integrations.
- Experience taking AI systems to production at enterprise scale, including evaluation, cost and performance tuning, and the security and governance requirements that gate deployment.
- Background working at or with a frontier lab or AI-native cloud provider, including an understanding of how they build, ship, and go to market.
- Track record of creating technical content that developers use, including reference architectures, deployment guides, blog posts, and conference presentations.
- Strong familiarity with modern development workflows and AI-assisted development tools such as Cursor, Claude Code, and Codex.
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.
About Databricks
Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn, X, YouTube, and Instagram.
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.
Skills Required
- 10+ years in field engineering, consulting, platform architecture, or AI systems development
- Depth in building and running AI systems in production across model serving, inference, retrieval, and agent frameworks
- Hands-on engineering skills: develop POCs, build demos, debug integrations
- Experience with Python
- Experience with REST APIs and SDKs
- Established relationships with product and engineering functions at major AI labs and cloud providers
- Experience in strategic technical partnerships and multi-company engineering initiatives
- Deep knowledge of the Databricks platform and ability to design cross-platform AI architectures
- Strong communication and influence skills for engineering teams and executives
- Availability to travel globally to partner sites, conferences, and events
- Prior experience in Partner Solutions Architect, Solutions Engineering, or Alliance Engineering roles
- Experience taking AI systems to production at enterprise scale, including cost/performance tuning and governance
- Background working at or with a frontier lab or AI-native cloud provider
- Track record of creating developer technical content (reference architectures, deployment guides, blog posts, presentations)
- Familiarity with AI-assisted development tools such as Cursor, Claude Code, and Codex
Databricks Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Databricks and has not been reviewed or approved by Databricks.
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Equity Value & Accessibility — Equity grants are a meaningful part of offers, and periodic tender opportunities and secondary options have made private equity more tangible for many employees. This perceived upside contributes to strong total-compensation sentiment in key roles.
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Healthcare Strength — Comprehensive medical, dental, and vision coverage is paired with mental‑health resources and wellness reimbursements, indicating a robust health package. Multiple summaries highlight broad coverage that employees can practically use.
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Leave & Time Off Breadth — Generous PTO, paid holidays/sick time, and fully paid parental leave are frequently described, with hybrid/remote flexibility common in the U.S. These policies expand time‑off accessibility across different life stages.
Databricks Insights
What We Do
As the leader in Unified Data Analytics, Databricks helps organizations make all their data ready for analytics, empower data science and data-driven decisions across the organization, and rapidly adopt machine learning to outpace the competition. By providing data teams with the ability to process massive amounts of data in the Cloud and power AI with that data, Databricks helps organizations innovate faster and tackle challenges like treating chronic disease through faster drug discovery, improving energy efficiency, and protecting financial markets.
