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The Solutions Architect (AI) team executes on Databricks’ strategic Product Operating Model that provides enhanced focus on earlier stage, highly prioritized product lines in order to establish product market fit, and set the course for rapid revenue growth. They are part of a global go-to-market team mandate, though individually will cover a specific, local region. Clients may span across one or more business units and verticals. By working in partnership with direct account teams, they will jointly engage clients, foster the necessary relationships, position in-depth the specific product line, so as to provide compelling reasons for clients to adopt and grow the usage of the given product. They understand the appropriate approach, the guardrails, and the steps needed to successfully adopt the product line, as clients deliver on their business objectives.
The Solutions Architect (AI) is paired with an Account Executive aligned to the product line with specific targets accordingly. Together, they will devise and implement a strategy across their assigned set of accounts, develop presentations, demos and other assets and deliver them such that customers make an informed decision as they decide to adopt the product-line in a meaningful way.
The impact you will have
- Provide technical leadership to guide strategic customers to successful implementations on big data projects, ranging from architectural design to data engineering to model deployment
- Collaborate with GTM leadership and account teams to design and execute high-impact engagement strategies and strategic sales plays across your territory, driving AI adoption
- As a trusted advisor, serve as an expert Solutions Architect building technical credibility with CAIOs, CDOs and CTOs to drive product adoption and vision.
- Enable clients at scale through workshops, POC execution, and developing customer-facing collateral that increases technical knowledge and demonstrates the value of the Databricks architecture for AI and agentic workflows.
- Lead the design and implementation of high-profile, high-value agentic AI use cases on Databricks, leveraging Databricks Agent Framework, AgentBricks, and other Databricks AI capabilities to accelerate production adoption and deliver measurable business outcomes.
- Drive agentic AI quality and production readiness by implementing robust evaluation and monitoring strategies using MLflow, LLM-as-a-judge, custom evaluation metrics, and tracing to continuously improve agent accuracy, reliability, and performance.
- Influence product roadmap by translating field-derived, data-driven insights into strategic recommendations for Product and Engineering teams.
- Handle the most complex technical challenges in this product line by acting as the tier-3 escalation point for the field, ensuring customer success in mission-critical use-cases.
- Establish and refine the sales qualification and POC intake process, ensuring well-scoped engagements that maximize customer success and minimize friction for R&D.
Competencies & Responsibilities
- 10+ years in a customer-facing, pre-sales or consulting role influencing technical executives, driving high-level ML/AI strategy and product adoption.
- Experience with design and implementation of production-grade ML and generative AI applications in customer or enterprise environments
- Hands-on experience designing, building, and deploying enterprise-grade agentic AI solutions, including RAG, tool calling, multi-agent orchestration, and autonomous workflows, ideally using Databricks Agent Framework and Agent Bricks.
- Strong understanding of agentic AI evaluation methodologies, including MLflow Tracing, LLM judges, custom scorers, and systematic approaches to measuring agent quality, reliability, and production performance.
- Deep familiarity with using frontier models (from providers such as Anthropic, OpenAI and Google Gemini), including deployment, optimisation and migration strategies as well as with machine learning, LLMs, and agentic AI workflows.
- Proficient in programming, debugging, and problem-solving using SQL, Python, Apache Spark, cloud platforms, and Lakehouse architectures and with AI tools.
- Experience collaborating with Global System Integrators (GSIs) and third-party consulting organizations to drive customer outcomes in AI.
- Hands-on experience building solutions within major public cloud environments (AWS, Azure, or GCP), with an understanding of cloud-native AI platforms
- Undergraduate degree (or higher) in a technical field such as Computer Science, Cybersecurity, Applied Mathematics, Engineering or similar.
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 a customer-facing, pre-sales, or consulting role influencing technical executives and driving ML/AI strategy and product adoption
- Experience designing and implementing production-grade machine learning and generative AI applications in enterprise environments
- Hands-on experience building and deploying enterprise-grade agentic AI solutions, including RAG, tool calling, multi-agent orchestration, and autonomous workflows
- Experience with Databricks Agent Framework and AgentBricks
- Understanding of agentic AI evaluation methodologies, including MLflow Tracing, LLM judges, custom scorers, and production performance measurement
- Familiarity with frontier models from Anthropic, OpenAI, and Google Gemini, including deployment, optimization, and migration strategies
- Programming, debugging, and problem-solving proficiency using SQL, Python, Apache Spark, cloud platforms, Lakehouse architectures, and AI tools
- Experience collaborating with Global System Integrators and third-party consulting organizations
- Hands-on experience building solutions in AWS, Azure, or GCP and understanding of cloud-native AI platforms
- Undergraduate degree or higher in Computer Science, Cybersecurity, Applied Mathematics, Engineering, or a related technical field
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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Healthcare Strength — Healthcare coverage is described as comprehensive, including medical, dental, and vision for employees and dependents, plus dedicated mental-health resources and an EAP. Wellness and gym reimbursements further support wellbeing.
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Equity Value & Accessibility — Equity grants (RSUs/stock options) are highlighted as a major part of compensation and are often viewed as attractive. Occasional tender-offer liquidity and performance bonuses reinforce total rewards.
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Parental & Family Support — Paid parental leave, fertility benefits, and subsidized backup dependent care are emphasized. Family medical leave and caregiver support also feature in the package.
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.
