Senior Forward Deployed Engineer - Government Data & AI

Databricks; Virginia (IL); Hybrid; USD 182,000 - 250,000; Full time

Job summary

Databricks is seeking a Sr. Forward Deployed Engineer to work with federal government customers, owning architecture and delivering end-to-end data and AI solutions on the Databricks platform.

This hands-on, customer-facing role requires travel to client sites 20-25% and a willingness to engage across engineering, product, and deployment teams. You will design scalable, secure architectures, train and integrate with client systems, and produce accelerators and reusable assets while maintaining a

Qualifications

• 6+ years experience in data engineering, data platforms, or software engineering.
• Fluency in Python, Scala, and JavaScript/TypeScript.
• Experience with two or more cloud ecosystems (AWS/Azure/GCP) and expertise in at least one.
• Deep experience with distributed computing using Apache Spark and Spark internals.
• Familiarity with CI/CD for production deployments; working with MLOps and AI models.
• Experience delivering technical projects to enterprise clients with stakeholder management.

Responsibilities

• Lead architecture and end-to-end solution delivery for government customers.
• Design production-grade data and AI applications.
• Collaborate with engineering, product, and customer teams to scope and deliver.
• Travel to client sites 20–25% as needed.
• Develop accelerators and reusable assets to scale impact across accounts.

Skills

Data engineering

Programming: Python/Scala/JS

Cloud platforms (AWS/Azure/GCP)

Apache Spark

CI/CD

MLOps / ML/AI

Project delivery / client-facing

Job description

Databricks is seeking a Sr. Forward Deployed Engineer to work with federal government customers, owning architecture and delivering end-to-end data and AI solutions on the Databricks platform.

This hands-on, customer-facing role requires travel to client sites 20-25% and a willingness to engage across engineering, product, and deployment teams. You will design scalable, secure architectures, train and integrate with client systems, and produce accelerators and reusable assets while maintaining a