Senior Databricks Forward Deployed Engineer (AI/ML)
New
R
RevStarData & AI Consulting
Florida, United States. Texas, United States. Arizona, United StatesFull-TimeSenior
Salary not disclosed
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Job Details
- Experience
- 5+ years
- Required Skills
- AWSMachine LearningMLFlowData engineeringSparkDatabricksLLMGenerative AIPySpark
Requirements
- 5+ years of hands-on experience in Data Engineering, Machine Learning, or Solutions Architecture.
- 3+ years of deep technical experience within the Databricks Ecosystem (Delta Lake, Unity Catalog, MLflow, Spark/PySpark, Databricks Workflows/Jobs, Mosaic AI).
- Practical experience designing and deploying RAG pipelines, fine-tuning LLMs, working with vector databases, and managing ML pipelines end-to-end.
- Strong expertise in cloud-native architectures (AWS preferred—S3, Glue, Lambda, Redshift, etc.).
- Proven track record of migrating enterprise legacy data warehouses/lakes onto Databricks.
- Demonstrated track record of leading technical delivery for Fortune 500 or large enterprise clients.
- Exceptional verbal and written communication skills.
- Comfortable presenting technical architecture, building POCs/demos, and managing client stakeholders up to the C-suite.
- Ability to spot technical expansion opportunities within existing client accounts.
- Databricks Certified Data Engineer Professional and/or Machine Learning Professional preferred.
Responsibilities
- Design, build, and deploy production-grade data pipelines, analytics engines, and Generative AI/LLM applications using Databricks and modern cloud platforms.
- Serve as the primary technical leader on strategic enterprise client engagements, partnering with C-suite executives and engineering teams.
- Lead complex legacy platform migrations (e.g., Snowflake, Teradata, Hadoop, SQL Server) onto the Databricks Lakehouse architecture.
- Guide enterprise customers in adopting GenAI solutions, RAG architectures, model fine-tuning, and MLflow/Databricks Mosaic AI integrations.
- Partner with account leadership to identify high-value technical use cases to expand Databricks platform usage and ROI.
- Mentor junior Solution Engineers, Architects, and Consultants while contributing to internal code libraries and best practices.
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