Synced from Greenhouse · 8d ago

Solutions Architect

DatabricksCentral - United States; West Coast - United StatesPosted Aug 14, 2026
Solutions ArchitectSenior
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Mirrored from Databricks's own Greenhouse careers system · refreshed hourly

$180k–$248k
Compensation
819
Other open Databricks roles
8d ago
Posted
Greenhouse
Applicant system
Job descriptionReq 8697991002

FEQ427R382

As a Specialist Solutions Architect (SSA) — AI/ML, you will serve as a trusted technical expert in Machine Learning and Artificial Intelligence for Databricks customers and our Field Engineering organization. Working 

This role offers an opportunity to work at the forefront of cutting-edge technologies—including Generative AI, LLMs, and MLOps—while mentoring peers and establishing yourself as a technical thought leader in the AI community.

The impact you will have: 

  • Architect AI/ML Workloads: Design and deploy production-level ML and AI architectures using the Databricks unified platform, including AI agents, end-to-end pipeline automation, and model training/inference optimization.
  • Lead GenAI Implementation: Act as a hands-on practitioner for enterprise Generative AI solutions, including Retrieval-Augmented Generation (RAG), tool-calling/multi-agent orchestration, guardrails, AI evaluation, and observability systems.
  • Optimize & Scale: Build and maintain scalable customer AI workloads, applying best-in-class MLOps practices across diverse industry domains.
  • Technical Pre-Sales Support: Partner with Solutions Architects during the sales cycle—guiding prospects through feature engineering, model tracking, serving, and monitoring within a single platform.
  • Influence the Product Roadmap: Translate customer feedback into actionable product insights by collaborating with Engineering and Product teams to shape the future of Databricks' AI offerings.

What we look for:

  • 5+ years of hands-on industry experience in at least one of the following domains:
    • ML Engineering: Building and maintaining cloud infrastructure (AWS, Azure, or GCP) supporting production ML applications and drift monitoring.
    • AI Engineering: Working with LLMs and agentic systems, including vector databases, fine-tuning, AI guardrails, and frameworks like LangChain, Hugging Face, or OpenAI APIs.
  • Demonstrated ability to translate complex AI/ML concepts for both technical and non-technical audiences.
  • Strong passion for continuous learning, cross-team collaboration, and delivering tangible business value through AI.
  • Understanding of modern lakehouse architectures (Delta Lake, data modeling, BI integration) across major cloud platforms (AWS, Azure, or GCP).
  • [Preferred] Prior experience in a pre-sales or post-sales technical consulting role.
  • Graduate degree in Computer Science, Engineering, Statistics, or a related quantitative field—or equivalent practical experience.
  • Ability to travel up to 30% as needed for customer engagements.
  • Ability to hit role-specific training and technical delivery milestones within the first 6 months.
  • Ability to travel up to 30% as needed for customer engagements.

 

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.

 

Local Pay Range
$180,000$247,500 USD

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.

Applicant Privacy Notice

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Based on publicly available information, candidates applying through greenhouse for roles at Databricks can typically expect an initial application review followed by a recruiter screening call, if selected. The process may include multiple stages such as a hiring manager conversation, technical or role-specific assessments, and panel interviews with team members, depending on the position applied for—whether technical, sales, or operational. Candidates for engineering or data-focused roles might encounter coding exercises or case studies, while business roles may involve situational or behavioral questions. Communication is commonly handled through email or the greenhouse portal, and response times vary based on team bandwidth and role seniority. Applicants can generally expect an emphasis on cultural fit and collaboration skills alongside role-specific competencies. Preparing clear examples of past achievements and understanding the company's products can help candidates feel more confident throughout the process.

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Solutions Architect
Databricks · Central - United States; West Coast - United States
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