[![Image]() Meet Jobicy Copilot — free AI autofill for job applications + remote job alerts ›](#) [All remote jobs](https://jobicy.com/jobs.md)Open role[![Databricks logo](https://jobicy.com/data/server-nyc0409/galaxy/mercury/2021/12/4e3f864ba9cf3c62d471e1c62414d098.jpg)](https://jobicy.com/company/databricks.md)Remote opportunity at[Databricks](https://jobicy.com/company/databricks.md) # AI Engineer – FDE (Forward Deployed Engineer) – U.S. Federal Sector Review the role, location requirements, compensation details, and application process before deciding whether this opportunity fits your next career move. [Apply for this job](#job-application)[View company](https://jobicy.com/company/databricks.md)Share7 Sep 2026Published37Listing views0Application actions7 Oct 2026Apply before Opportunity details ## About this role. AI SummaryDatabricks is seeking a senior customer-facing AI Forward Deployed Engineer to deliver and productionize Generative AI applications for U.S. federal-sector customers. The role combines hands-on engineering with technical advisory work, including RAG, multi-agent systems, Text2SQL, fine-tuning, evaluation, and cloud ML deployment. The engineer will lead production rollouts, collaborate with product and engineering teams, and communicate complex AI concepts to varied customer audiences. U.S. citizenship and eligibility for a Secret clearance are mandatory, with periodic on-site work and customer travel in the Washington, D.C., Maryland, and Virginia area. ## Role DNA A quick view of the complexity, pace, ownership and collaboration implied by the job description. ### Job Complexity 5/5EasyHard ### Pace & Pressure 5/5RelaxedFast-paced ### Autonomy Level 5/5GuidedFull ownership ### Communication Load 5/5IndependentCollaborative AI insightThis is a highly senior role requiring deep applied GenAI, production ML, cloud engineering, and customer-delivery expertise. Federal-sector eligibility, ownership of production outcomes, and frequent cross-functional and client communication add substantial complexity. ## Salary analysis Estimated compensation compared with the broader US market for similar roles. Estimated job medianMarket rate$216,104US market range$180k–$260k0$286k AI insightThe disclosed annual USD pay range is $182,000 to $250,208, with a midpoint of $216,104. This is competitive for a senior U.S. AI/ML forward-deployed engineering role requiring production GenAI expertise, customer engagement, federal eligibility, and travel; the estimated broader U.S. market range is $180,000 to $260,000 annually, excluding bonus and equity. ## Core skills Skills and capabilities most closely associated with this opportunity. [Generative AI](https://jobicy.com/jobs?search_keywords=Generative%20AI.md)[LLMOps](https://jobicy.com/jobs?search_keywords=LLMOps.md)[Retrieval-Augmented Generation](https://jobicy.com/jobs?search_keywords=Retrieval-Augmented%20Generation.md)[Multi-Agent Systems](https://jobicy.com/jobs?search_keywords=Multi-Agent%20Systems.md)[Machine Learning](https://jobicy.com/jobs?search_keywords=Machine%20Learning.md)[Python](https://jobicy.com/jobs?search_keywords=Python.md)[PyTorch](https://jobicy.com/jobs?search_keywords=PyTorch.md)[AWS](https://jobicy.com/jobs?search_keywords=AWS.md)[Azure](https://jobicy.com/jobs?search_keywords=Azure.md)[GCP](https://jobicy.com/jobs?search_keywords=GCP.md) Sample interview questionsDescribe a production GenAI application you built and the business problem it solved.I would explain the user problem, system architecture, model and retrieval choices, evaluation approach, deployment process, and measurable outcomes such as quality, latency, adoption, or cost improvements. I would also describe how I monitored the application and iterated after launch. How would you design a secure RAG solution for a federal customer handling sensitive information? I would begin with data classification, identity-based access controls, encryption, audit logging, and network isolation. I would enforce document-level authorization during retrieval, minimize sensitive data exposure in prompts and logs, evaluate model and retrieval behavior for leakage risks, and align the deployment with the customer’s compliance and clearance requirements. What framework would you use to evaluate and improve a GenAI application in production? I would define task-specific quality metrics, create representative offline test sets, and combine automated evaluations with structured human review. In production, I would monitor latency, cost, retrieval relevance, safety signals, user feedback, and task success, then use error analysis to prioritize prompt, retrieval, model, or workflow improvements. How do you communicate technical AI tradeoffs to a non-technical stakeholder? I focus first on the stakeholder’s objective, risk tolerance, and success metrics, then present options in terms of business impact, reliability, cost, timeline, and operational risk. I avoid unnecessary jargon, use concrete examples or prototypes, and make a clear recommendation while documenting assumptions and decisions. How would you approach deploying an ML or GenAI workload across AWS, Azure, or GCP? I would use infrastructure as code, automated CI/CD, secure secrets management, observability, and reproducible model and data versioning. I would select managed or containerized services based on performance, governance, portability, and customer constraints, then validate the release through staged environments, load testing, monitoring, and rollback procedures. 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. The position is based in the Washington, D.C., Maryland, or Virginia metropolitan area and includes periodic on‑site work and client collaboration. Candidates with an active Secret or higher clearance are strongly encouraged to apply. The AI Forward Deployed Engineering (AI FDE) team is a highly specialized customer-facing AI team at Databricks. We deliver professional services engagements to help our customers build and productionize first-of-its-kind AI applications. We work cross-functionally to shape long-term strategic priorities and initiatives alongside engineering, product, and developer relations, as well as support internal subject matter expert (SME) teams. We view our team as an ensemble: we look for individuals with strong, unique specializations to improve the overall strength of the team. This team is the right fit for you if you love working with customers, teammates, and fueling your curiosity for the latest trends in GenAI, LLMOps, and ML more broadly. This role can be remote. The impact you will have: * Develop cutting-edge GenAI solutions, incorporating the latest techniques from [Databricks AI research](https://www.databricks.com/blog/category/databricks-ai?categories=databricks-ai%2Cai-research%2Cai-engineering) to solve customer problems * Own production rollouts of consumer and internally facing GenAI applications * Serve as a trusted technical advisor to customers across a variety of domains * Present at conferences such as [Data + AI Summit](https://www.databricks.com/dataaisummit), recognized as a thought leader internally and externally * Collaborate cross-functionally with the product and engineering teams to influence priorities and shape the product roadmap What we look for: * Experience building GenAI applications, including RAG, multi-agent systems, Text2SQL, fine-tuning, etc., with tools such as HuggingFace, LangChain, and DSPy * Expertise in deploying production-grade GenAI applications, including evaluation and optimizations * Extensive years of hands-on industry data science experience, leveraging common machine learning and data science tools, i.e. pandas, scikit-learn, PyTorch, etc. * Experience building production-grade machine learning deployments on AWS, Azure, or GCP * Graduate degree in a quantitative discipline (Computer Science, Engineering, Statistics, Operations Research, etc.) or equivalent practical experience * Experience communicating and/or teaching technical concepts to non-technical and technical audiences alike * Passion for collaboration, life-long learning, and driving business value through AI * [Preferred] Experience using the Databricks Intelligence Platform and Apache Spark™ to process large-scale distributed datasets * Willing to travel once every 4-8 weeks to see customers (as needed) 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](https://www.databricks.com/sites/default/files/2024-08/us-pay-zone-mapping.pdf). Local 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](https://www.linkedin.com/company/databricks), [X](https://x.com/databricks), [YouTube](https://www.youtube.com/@Databricks), and [Instagram](https://www.instagram.com/databricksinc/?hl=en). 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](https://docs.google.com/document/d/154un3e8Xav4BceOSlcYFZRGEuQI54xMxVydRwQn54eQ/edit?usp=sharing). 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. 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