Senior Databricks Forward Deployed Engineer (AI/ML)
New
R
RevStarData and AI consulting
Source API remote eligibility restrictions: United StatesFull-TimeSenior
Salary not disclosed
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Job Details
- Experience
- 5+ years of hands-on experience in Data Engineering, Machine Learning, or Solutions Architecture; 3+ years of deep technical experience within the Databricks Ecosystem
- Required Skills
- AWSPythonMLFlowSparkDatabricksGenerative AIPySpark
Requirements
- Have 5+ years of hands-on experience in Data Engineering, Machine Learning, or Solutions Architecture.
- Have 3+ years of deep technical experience within the Databricks ecosystem, including Delta Lake, Unity Catalog, MLflow, Spark/PySpark, Databricks Workflows/Jobs, and Mosaic AI.
- Have practical experience designing and deploying RAG pipelines, fine-tuning LLMs, working with vector databases, and managing ML pipelines end-to-end.
- Bring strong expertise in cloud-native architectures; AWS is preferred, including services such as S3, Glue, Lambda, and Redshift.
- Have a proven track record migrating enterprise legacy data warehouses or lakes to Databricks.
- Have experience leading technical delivery for Fortune 500 or large enterprise clients.
- Be comfortable presenting technical architecture, building POCs and demos, and managing client stakeholders up to the C-suite.
- Databricks Certified Data Engineer Professional and/or Machine Learning Professional certifications are preferred.
- Healthcare, Retail, or Consumer Goods experience is a strong plus.
Responsibilities
- Design, build, and deploy production-grade data pipelines, analytics engines, and Generative AI/LLM applications using Databricks, Spark, Python/PySpark, and cloud ecosystems.
- Lead technical delivery for strategic enterprise client engagements and translate business challenges into technical solutions.
- Migrate legacy platforms, including Snowflake, Teradata, Hadoop, and SQL Server, to the Databricks Lakehouse architecture.
- Guide enterprise customers in adopting GenAI solutions, RAG architectures, model fine-tuning, and MLflow/Databricks Mosaic AI integrations.
- Identify high-value technical use cases across client business units to expand Databricks platform usage.
- Mentor and coach junior Solution Engineers, Architects, and Consultants.
- Contribute to internal code libraries, reusable accelerators, and technical delivery best practices.
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