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Databricks

Specialist Solutions Architect - AI/ML

Databricks is hiring a Specialist Solutions Architect - AI/ML for a remote role open to applicants in United States. It pays $180k-$248k a year and Level rates it ; you can apply on Databricks.

Level's read on this job

  • Works on AI ●●●○ is how Level rates this solutions architect role: the daily work is on AI products, without building the model.
  • Pay on this posting starts 7% higher than the typical solutions architect posting on Level.
  • This is listed as a remote role.
  • The posting mentions OpenAI, LangChain and Hugging Face among its tools and skills.
  • Databricks has 908 other open roles on Level.

AI in this role

Specialist Solutions Architect driving advanced AI/ML technical strategy, RAG architectures, and agentic systems adoption at Databricks.

openailangchainhugging-facepythonsqlhuggingfaceopenai-apisawsazuregcp
ragfine-tuningai-evaluationsolutions-architectureai-engineeringmachine-learningmulti-agent-systems

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As an AI/ML Specialist Solutions Architect (SSA), you will lead the advanced AI/ML technical strategy for your customers — owning complex architecture discussions, driving platform adoption, and serving as a trusted advisor to customer technical leads and architects. You combine deep technical expertise with strategic thinking to position Databricks as the foundation of your customers’ data and AI strategy. You are further developing a technical specialization and are recognized within the Field Engineering team for depth in the specific domain.

This position can be remote. 

The Impact You Will Have

  • Own the end-to-end AI/ML technical strategy for your accounts, from discovery through production deployment and consumption growth
  • Lead complex architecture discussions — designing scalable, production-grade solutions spanning AI/ML, including Retrieval-Augmented Generation (RAG), tool calling, multi-agent orchestration, guardrails, AI evaluation, and observability systems
  • Serve as a trusted technical advisor to customer architects, engineering leads, and Directors
  • Drive technical wins in competitive scenarios by demonstrating Databricks’ differentiation through custom-built solutions
  • Develop and declare an emerging technical specialization (archetype) — becoming a go-to resource for your team in that domain
  • Orchestrate cross-functional resources (DSAs, SAs, Partners) to deliver comprehensive solutions for complex customer needs
  • Influence product direction by providing structured feedback on customer requirements and competitive gaps

What We Look For

  • 6+ years in solutions architecture, technical pre-sales, or a senior hands-on technical role in the following areas:
    • 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
  • Strong coding proficiency in Python and SQL — you must demonstrate live coding, debugging, and solution-building skills
  • Deep expertise in distributed data systems architecture: designing scalable pipelines, streaming architectures, lakehouse patterns, and cloud-native data platforms
  • Proficient on the Databricks Platform (or demonstrated ability to achieve proficiency rapidly) with a developing technical specialization in one area (e.g., real-time/streaming, ML/AI, data governance, migrations)
  • Proven ability to lead architecture discussions with senior technical stakeholders — whiteboarding, design reviews, and trade-off analysis
  • Experience with production deployments on public cloud (AWS, Azure, or GCP), including infrastructure, security, and governance considerations
  • Track record of driving platform adoption and consumption growth within accounts
  • Excellent communication skills — able to translate complex architectures into business value for both technical and executive audiences
  • Bachelor's or Master's degree in Computer Science, Engineering, or a quantitative discipline (or equivalent experience)
  • Willingness to travel up to 30% as needed

Nice to Have

  • Databricks certifications (Data Engineer, ML, Platform)
  • Experience with competitive platforms (Snowflake, AWS native services, Azure Synapse) — understanding the landscape you'll position against
  • Background in a data/AI company or cloud provider
  • Industry domain expertise (Financial Services, Healthcare, Retail, Media, etc.)

 

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.

How we rate this

Specialist Solutions Architect - AI/ML at Databricks rates 75 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

RAGFine-tuningAI EvaluationSolutions ArchitectureAI EngineeringMachine learningMulti Agent SystemsOpenAI

Also common in solutions architect jobs at this level

Pay

This job starts at
$180k
Typical solutions architect job
$169k

This posting starts 7% above the typical solutions architect job. See solutions architect jobs

Questions you could be asked

  1. How would you design a retrieval step so the model answers from real data instead of guessing?
  2. Walk me through fine-tuning a model: what data did you use, and how did you check the result?
  3. How do you decide that one model's output is better than another's for a given task?
  4. Tell me about a project where solutions architecture was part of your work. What did you do?
  5. Tell me about a project where ai engineering was part of your work. What did you do?

Adapt your resume

  • List these exact terms on your resume: RAG, Fine-tuning, AI Evaluation, Solutions Architecture, and AI Engineering. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
  • Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.

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