Level

Databricks

Sr. Forward Deployed Engineer - National Security

Databricks is hiring a Sr. Forward Deployed Engineer - National Security in Boston, New York and Washington DC, United States. It pays $182k-$250k a year and Level rates it ; you can apply on Databricks.

Level's read on this job

  • On Level's scale, this forward deployed engineer role is Works on AI ●●●○: the daily work is on AI products, without building the model.
  • The listed pay starts close to the typical forward deployed engineer posting on Level.
  • The posting allows some remote work.
  • Tools and skills the posting cites include MLOps, data engineering and machine learning.
  • Level lists 894 other open roles at Databricks.

AI in this role

Builds and productionizes data and AI solutions for federal government customers using the Databricks platform.

ml-opsdata-engineeringmachine-learningpythonsolution-architecture

ADD REQ ID

CSQ427R88

PLEASE NOTE: Due to federal contract requirements and client site access obligations, U.S. citizenship and eligibility for a U.S. government secret clearance are required to access classified information. Candidates with an active Secret or higher clearance are strongly encouraged to apply.

About Databricks

At Databricks, we are passionate about enabling data teams to solve the world's toughest problems, from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers, and customer obsessed, we leap at every opportunity to solve technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started.

The Role

As a Sr. Forward Deployed Engineer (FDE), you will work with federal government customers to build and productionize solutions to their data & AI challenges using the Databricks platform. You will own the architecture, lead design decisions, and implement end-to-end systems spanning data engineering, AI, and application development. We work cross-functionally to shape long-term strategic priorities and initiatives alongside engineering, product, and developer relations. FDEs deliver with customer empathy, integrating with client systems, training, and other technical needs to help customers get most value out of their data. 

This is a hands-on, customer-facing role for builders who thrive at the intersection of technology and business impact. The ideal candidate combines engineering expertise with adaptability, curiosity, and a passion for working with customers and teammates to solve complex problems that drive measurable outcomes. FDEs are billable and know how to complete projects according to specification with exceptional customer empathy.

Please note: this role is hybrid and has a requirement to travel to customer locations 20-25% of the time 

The impact you will have:

  • Production Solution Delivery: Lead impactful customer technical projects by delivering production-grade systems, designing and building reference architectures, custom applications and data ingestion and ML/AI model integration
  • Transformational Impact: Guide strategic customers as they implement transformational big data projects including end-to-end design, build and deployment of industry-leading big data and AI applications. Work with engagement managers to scope technical delivery work with input from the customer
  • Empower Customers: Guide customers on architecture and design; bootstrap or implement customer projects which leads to a customers' successful understanding, evaluation and adoption of Databricks.
  • Own the Architecture: Lead architecture and design decisions, ensuring solutions are secure, scalable, and aligned with both customer needs and Databricks best practices.
  • Deliver Technical Components: Work with the Databricks technical team, Project Manager, Architect and Customer team to ensure the technical components of the engagement are delivered to meet customer's needs
  • Cross-Collaborate: Work with Engineers and Customer Support to provide product and implementation feedback and to guide rapid resolution for engagement specific product and support issues
  • Customer Immersion: Embed with customer teams, engaging with stakeholders from technical ICs to executives to deeply understand challenges and deliver impact.
  • Reusable Assets & Scale: Contribute accelerators, frameworks, and best practices that scale impact across accounts and influence the Databricks product roadmap.

What We're Looking For:

        Minimum Qualifications:

  • 6+ years experience in data engineering, data platforms & analytics, or software engineering
  • Fluency in writing code in 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 deploymentsWorking knowledge of MLOps, ML/AI models and AI APIsDesign 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, documentation and white-boarding skillsExperience working with enterprise clients and managing conflicts across a broad stakeholder range

    Preferred Qualifications:

  • Expertise in MLOps, ML/AI models, and AI APIs
  • Databricks Certification

 

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 base 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 anticipated 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.

 

Zone 1 Pay Range$182,000—$250,208 USDZone 2 Pay Range$182,000—$250,208 USDZone 3 Pay Range$182,000—$250,208 USDZone 4 Pay Range$182,000—$250,208 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

Sr. Forward Deployed Engineer - National Security at Databricks rates 70 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

ML OpsData EngineeringMachine learningPythonSolution Architecture

Also common in forward deployed engineer jobs at this level

Pay

This job starts at
$182k
Typical forward deployed engineer job
$182k

This posting starts close to the typical forward deployed engineer job. See forward deployed engineer jobs

Questions you could be asked

  1. How do you monitor a model once it's live, and how do you know it needs retraining?
  2. Tell me about a project where data engineering was part of your work. What did you do?
  3. Tell me about a project where machine learning was part of your work. What did you do?
  4. Tell me about a project where python was part of your work. What did you do?
  5. Tell me about a project where solution architecture was part of your work. What did you do?

Adapt your resume

  • List these exact terms on your resume: ML Ops, Data Engineering, Machine learning, Python, and Solution Architecture. 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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