Role: Databricks
Location: Remote(travel required)
Duration: 12+ months
Exp: 14+ years
About the role
You embed with a customer’s team and build. Not slideware, not a reference architecture — working agents, in their environment, against their real data, used by their real people, in weeks rather than quarters.
Forward deployed means exactly that: you sit where the problem is. You will learn a customer’s domain fast enough to be useful, write the code, wire up the integrations nobody documented, watch users struggle with v1, and ship v2 the same week. When a pilot proves out, you make it production-worthy and hand it over cleanly.
This role suits engineers who are energized by ambiguity, allergic to hand-waving, and happier shipping something imperfect on Friday than designing something perfect by Q3.
What you will do
- Embed directly with customer teams — engineering, operations, or a specific line of business — to understand the workflow in enough detail to automate it honestly.
- Build agents and AI applications end to end: prompt and tool design, ADK-based agents, retrieval pipelines, connectors to internal APIs and legacy systems, evaluation harnesses, and the UI or channel integration (chat, ticketing, internal portal) users will actually touch.
- Do the integration work others avoid: undocumented APIs, SOAP endpoints, flat-file drops, SAP and mainframe extracts, screen-scraped systems of record, custom auth schemes.
- Run tight build-measure-iterate loops with real users; instrument everything and let usage data settle arguments.
- Harden what works — error handling, retries, observability, cost controls, latency budgets, security review, deployment automation — and transition it to the customer’s team with documentation and pairing, not a hand-off email.
- Be the customer’s fastest feedback channel into the product and practice: file the sharp edges, build the workarounds, contribute reusable components back to internal libraries.
- Take on unglamorous debugging when a production agent misbehaves, including out-of-hours when the customer’s business depends on it.
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
- 10+ 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, Google Cloud Platform) 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.
Thanks,
Mahesh
Metanlytics
Recruiting-Manager
Direct number +1
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