Role at a glance
- Salary
- $180K – $247.5K/yr
- Location
- United States Remote - US - Arizona
- Work arrangement
- On-site
- Employment
- Full-time
- Experience
- 5+ years of hands-on industry experience
- Education
- Graduate degree in Computer Science, Engineering, Statistics, or a related quantitative field—or equivalent practical experience.
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Role Summary
The Specialist Solutions Architect — AI/ML serves as a technical expert in Machine Learning and Artificial Intelligence for Databricks customers and the Field Engineering organization. The role focuses on designing production AI/ML architectures, implementing Generative AI solutions, supporting technical pre-sales, and shaping Databricks' AI offerings through customer feedback.
What You'll Do
- Design and deploy production-level ML and AI architectures using the Databricks unified platform.
- Implement enterprise Generative AI solutions, including RAG, tool-calling/multi-agent orchestration, guardrails, AI evaluation, and...
- Build and maintain scalable customer AI workloads using MLOps practices.
- Partner with Solutions Architects during the sales cycle on feature engineering, model tracking, serving, and monitoring.
- Collaborate with Engineering and Product teams to translate customer feedback into product insights.
Generated from the employer's posting. Verify important details before applying.
View full postingQualifications
5+ years of hands-on industry experience in ML Engineering or AI Engineering; experience with cloud infrastructure, production ML applications, drift monitoring, LLMs, agentic systems, vector databases, fine-tuning, AI guardrails, LangChain, Hugging Face, OpenAI APIs, lakehouse architectures, Delta Lake, data modeling, and BI integration; ability to translate complex AI/ML concepts for technical and non-technical audiences; ability to travel up to 30%.
Required
- 5+ years of hands-on industry experience in ML Engineering or AI Engineering
- Cloud infrastructure using AWS, Azure, or GCP
- Production ML applications and drift monitoring
- LLMs and agentic systems
- Vector databases, fine-tuning, and AI guardrails
- Ability to translate complex AI/ML concepts for technical and non-technical audiences
- Understanding of modern lakehouse architectures, Delta Lake, data modeling, and BI integration
- Ability to travel up to 30% as needed for customer engagements
Preferred
- Prior experience in a pre-sales or post-sales technical consulting role
Original job description
Content provided by the employer
Original job description
Content provided by the employer
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.
- ML Engineering: Building and maintaining cloud infrastructure (AWS, Azure, or GCP) supporting production ML applications and drift monitoring.
- 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.
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.
About the company
Databricks
Large Enterprise
Databricks is a cloud-based data platform that specializes in providing solutions for data engineering, machine learning, and analytics. Founded in 2013 by the original creators of Apache Spark, the company enables organizations to unify data processing and analysis workflows, facilitating collaboration for data professionals. Databricks offers an integrated environment for data scientists, engineers, and business analysts, streamlining the process of building and deploying AI and data-driven applications. With a strong emphasis on simplifying big data management, Databricks helps businesses harness the power of their data to drive innovation and insights.
Databricks is a cloud-based data platform that specializes in providing solutions for data engineering, machine learning, and analytics. Founded in 2013 by the original creators of Apache Spark, the company enables organizations to unify data processing and analysis workflows, facilitating collaboration for data professionals. Databricks offers an integrated environment for data scientists, engineers, and business analysts, streamlining the process of building and deploying AI and data-driven applications. With a strong emphasis on simplifying big data management, Databricks helps businesses harness the power of their data to drive innovation and insights.