Staff Forward Deployed Engineer

About the role

Databricks is hiring a remote Staff Forward Deployed Engineer in India to lead big data and AI implementations for customers in its Professional Services team.

<p>Databricks provides a unified data and AI platform used by more than 20,000 organisations. This Staff Forward Deployed Engineer role sits in its Professional Services team and is listed as remote within India.</p><p>You will act as a trusted advisor to customers on big data and AI work across multiple clouds, build reusable automation tools that several customers can adopt, and bring AI problem-solving with sound guardrails. The role also covers third-party migrations, reference architectures and guiding several projects at once.</p><p>This listing was verified on the employer's own careers page on 6 October 2026. Please read the full posting and apply directly on the employer's site; Cloud Soft Solutions does not handle applications for this role.</p>

Responsibilities

<ul><li>Contribute to customer big data projects through reference architectures, how-to guides and production-ready tools</li><li>Advise strategic customers on major data initiatives, including third-party migrations and building big data and AI applications</li><li>Provide architecture and design expertise to support adoption and integration of Databricks</li><li>Work with Engineering and Customer Support to share feedback, resolve engagement issues and improve the product</li><li>Manage several projects at once against well-architected principles, spotting and reducing risks early</li><li>Build scalable automation utilities that can be reused across customers and industries</li></ul>

Requirements & qualifications

<ul><li>15+ years working with Spark, Kafka, cloud-native tooling and data lakes, in post-sales, architecture or consulting roles facing customers</li><li>6+ years working independently on big data architectures</li><li>2+ years on AI implementations involving RAG, MCP or context engineering</li><li>Strong experience in the Databricks ecosystem and coding in Python or Scala</li><li>Experience across GCP, AWS or Azure, along with documentation and whiteboarding skills</li><li>Strong problem-solving and stakeholder management with both technical and domain experts</li></ul>

Why this role in 2026

<p>This is a senior, remote FDE role that pairs deep big data experience with current GenAI patterns such as RAG and MCP. It suits experienced architects who want to build reusable tools across many customers rather than focus on a single account.</p>

Application tips

<ul><li>Make your years of customer-facing big data work easy to verify, since the posting sets a high bar</li><li>Describe specific RAG, MCP or context engineering implementations and how you handled guardrails</li><li>Show reusable tools or accelerators you built that more than one customer adopted</li><li>Include migration projects, especially moves from third-party platforms</li><li>Note your Databricks ecosystem experience and Python or Scala work clearly</li></ul>

Interview preparation

<p>Prepare for deep architecture conversations on Spark, streaming with Kafka and data lake design, plus how you would build a secure RAG or agent solution on a data platform. Expect questions on running several engagements in parallel and managing risk. Useful reading: our <a href="/interview-questions/rag-interview-questions-2026/">RAG interview questions</a> and <a href="/interview-questions/agentic-ai-interview-questions-2026/">agentic AI interview questions</a>.</p>

Career growth

<p>At staff level, the role's influence comes from reusable assets and product feedback across many customers. That experience is relevant to principal architecture, technical leadership in professional services and AI platform strategy roles.</p>