Director, Data Science & AI Engineering
Tasks
- Build and manage multidisciplinary data science and MLOps teams
- Create scalable AI governance evaluation and security frameworks
- Deliver dashboards and business intelligence reporting
- Design deploy and optimize LLM powered applications
- Develop agent based AI workflows with human oversight
- Develop data modeling and lakehouse warehouse strategy
- Establish MLOps and LLMOps engineering standards
- Implement Retrieval-Augmented Generation (RAG) systems
- Integrate AI applications with business systems
- Lead enterprise data science analytics and AI engineering strategy
- Manage prompt and model versioning and automated testing
- Monitor performance drift latency and cost
Perks/Benefits
- N/A
Skills/Tech-stack
Artificial Intelligence | Automated testing | Business Intelligence | CI/CD | Cloud infrastructure | Cost Tracking | Dashboards | Data Governance | Data Modeling | Data Warehousing | Drift Detection | Embeddings | Fine Tuning | Hybrid search | Incident Management | Infrastructure as Code | LLMOps | Lakehouse | Language Models | Large Language Models | Latency tracking | MLOps | Machine Learning | Model Context Protocol | Model Evaluation | Model versioning | Observability | Performance Monitoring | Prompt engineering | Retrieval-Augmented Generation | Security | Source Control | Vector Databases | “as-code”
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
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