This role is for senior engineers who can own GenAI delivery end to end on Databricks. You will work directly with enterprise clients to design, build, and deploy production‑grade GenAI systems using LLMs and retrieval‑based architectures. The work is hands‑on, customer‑facing, and focused on real business impact.
Key Responsibilities
- Design and deliver end‑to‑end GenAI applications on Databricks
- Build RAG systems that connect LLMs to enterprise data sources
- Implement vector search and LLM orchestration frameworks
- Productionize GenAI systems using CI/CD, MLflow, and data pipelines
- Advise client teams on architecture, governance, and GenAI best practices
Requirements
Must have:
- 5 plus years in ML engineering, data engineering, or AI systems
- 1 to 2 plus years building production GenAI or RAG applications
- Strong hands‑on experience with Databricks (Spark, MLflow, Unity Catalog)
- Python expertise with LLM frameworks (LangChain or similar)
- Experience deploying AI systems on AWS, Azure, or GCP
Nice to have:
- Databricks certifications (ML Engineer, GenAI Engineer, or Data Engineer)
- Prior consulting or customer‑facing delivery experience
- Experience with multiple vector databases