Level

Databricks

Forward Deployed Engineering - Senior Architect

AI in this role

Leads architecture and builds production-grade big data and AI solutions on the Databricks platform for customers.

ml-opssoftware-architecturedata-engineeringmachine-learningai-integration

As a Forward Deployed Engineer (FDE) you will work with 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.

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.
  • 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.
  • Work with Engineering and Databricks 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 look for:

  • Strong years 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
  • Build skills in technical areas, and demonstrate curiosity, adaptability, and eagerness to explore new technologies which support the deployment and integration of Databricks-based solutions to complete customer projects.
  • Travel to customers 20% of the time
  • Databricks Certification preferred but not essential

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

Forward Deployed Engineering - Senior Architect at Databricks rates 65 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. Open the description and count.

Prepare for this job

A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

ML OpsSoftware ArchitectureData EngineeringMachine LearningAI Integration

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 software architecture was part of your work. What did you do?
  3. Tell me about a project where data engineering was part of your work. What did you do?
  4. Tell me about a project where machine learning was part of your work. What did you do?
  5. Tell me about a project where ai integration was part of your work. What did you do?

Adapt your resume

  • List these exact terms on your resume: ML Ops, Software Architecture, Data Engineering, Machine Learning, and AI Integration. 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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