Senior Forward Deployed Engineer — Data & AI Solutions

FDE Times; Washington (District of Columbia); On-site; USD 182,000 - 250,000; Full time

Job summary

Databricks is hiring a Sr. Forward Deployed Engineer to lead production-grade data and AI projects for enterprise customers in the United States.

You will own architecture, drive design decisions, and deliver end-to-end systems spanning data engineering, ML/AI model integration, and application development. Responsibilities include guiding customers through end-to-end design, building reference architectures, and ensuring secure, scalable deployments while collaborating across engineering,

Qualifications

• 6+ years experience in data engineering, data platforms & analytics, or software engineering.
• Comfortable writing code in Python, Scala, JavaScript/TypeScript and modern frameworks.
• Working knowledge of two or more Cloud ecosystems (AWS, Azure, GCP) with expertise in at least one.

Responsibilities

• Lead production-grade solution delivery by designing reference architectures and data ingestion and ML/AI model integration.
• Guide strategic customers through end-to-end design, build and deployment of big data and AI applications.
• Own architecture decisions to ensure secure, scalable solutions aligned with customer needs and Databricks best practices.
• Collaborate with Databricks engineering, product, and customer teams to deliver required components.

Skills

Data engineering

Apache Spark

Python

Scala

JavaScript/TypeScript

Cloud (AWS/Azure/GCP)

Enterprise delivery

Tools

Apache Spark

Databricks

CI/CD

ML/AI models

Job description

Databricks is hiring a Sr. Forward Deployed Engineer to lead production-grade data and AI projects for enterprise customers in the United States.

You will own architecture, drive design decisions, and deliver end-to-end systems spanning data engineering, ML/AI model integration, and application development. Responsibilities include guiding customers through end-to-end design, building reference architectures, and ensuring secure, scalable deployments while collaborating across engineering,