Sr. Forward Deployed Engineer (FDE) - Digital Native Business
Databricks Mosaic · West Coast - United States · Remote - California
CHECKED 15H AGO
Infrastructureremotesenior$182k–$250k
At a glance
Highlights
- Build and productionize end-to-end data and AI solutions for customers.
- Own architecture for production-grade systems and reference architectures.
- Embed with customer teams to drive measurable business outcomes.
What they offer
- annual performance bonus
- equity
- comprehensive benefits
Ideal candidate
Hands-on builder with 6+ years in data or software engineering who thrives where technology meets business impact. Customer-empathetic, adaptable and curious, passionate about embedding with clients to solve complex problems.
Requirements
- 6+ years of experience in data engineering, data platforms & analytics, or software engineering
- Comfortable writing code in either Python, Scala, JavaScript/TypeScript, and modern frameworks
- Working knowledge of two or more common Cloud ecosystems (AWS, Azure, GCP) with expertise in at least one
- Deep experience with distributed computing with Apache Spark and knowledge of Spark runtime internals
- Familiarity with CI/CD for production deployments
- Working knowledge of MLOps, ML/AI models and AI APIs
- Design and deployment of performant production end-to-end data architectures and applications that combine data pipelines, ML/AI models, and user-facing interfaces
- Experience with technical project delivery - managing scope, timelines and measurable outcomes, translating complex concepts into actionable solutions
- Documentation and white-boarding skills
- Experience working with enterprise clients and managing conflicts across a broad stakeholder range
- remote policy
- Based in San Francisco Bay Area or able to travel there at least one week per month
Lab profile
About Databricks Mosaic
Builds unified data analytics and AI platform to productionize AI applications.
What they build
- Databricks platform
- Unified Data Analytics and AI
- AI platform
Known for
- Forward-deployed AI engineering
- Productionizing first-of-kind AI applications
- Customer platform adoption and scale
- Cross-functional engineering and product collaboration