Databricks Forward Deployed Engineer (AI/ML)

Excerpt from the original posting

At RevStar, we build cutting-edge cloud, data, and Generative AI solutions that transform how enterprise organizations operate. As a strategic partner in the AWS and Databricks ecosystems, we don’t just deliver code—we solve complex business problems, modernize legacy data estates, and deploy production-grade AI applications that drive real business value.
Role Overview
We are seeking a Senior Databricks Forward Deployed Engineer (FDE) to join our growing Data & AI Practice. In this highly visible role, you will work embedded directly at the intersection of technical architecture, hands-on engineering, and executive client engagement.
As an FDE, you are both a master builder and a trusted technical advisor. You will own the full delivery lifecycle for high-impact enterprise accounts—designing scalable data foundations, implementing cutting-edge Generative AI solutions, and migrating complex workloads onto the Databricks Lakehouse platform. Simultaneously, you will drive customer adoption and consumption growth by identifying new use cases and building strategic alignment with client technical leadership.
Our Core Values: 
- Self-Mastery : We hold a high bar for how we think, communicate, and improve.
- Ownership : We own outcomes, not just effort.
- Shared Destiny : We rise or fall together.

Key Responsibilities
- Hands-on Solution Architecture & Engineering : Design, build, and deploy production-grade data pipelines, analytics engines, and Generative AI/LLM applications using the Databricks platform, Spark, Python/PySpark, and modern cloud ecosystems (AWS/Azure/GCP).
- Enterprise Customer Delivery : Serve as the primary technical leader on strategic enterprise client engagements. Partner with C-level executives, VP/Directors of Data, and engineering teams to translate business challenges into high-performing technical solutions.
- Databricks Migration & Estate Modernization : Lead complex legacy platform migrations (e.g., Snowflake, Teradata, legacy Hadoop, SQL Server) onto the Databricks Lakehouse architecture.
- GenAI & Advanced Analytics Implementation: Guide enterprise customers (Healthcare, Retail, Financial Services, etc.) in adopting GenAI solutions, RAG architectures, model fine-tuning, and MLflow/Databricks Mosaic AI integrations.
- Drive Platform Adoption & Growth: Partner with account leadership to identify new, high-value technical use cases across client business units, expanding Databricks platform usage and driving measurable ROI for clien…

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