Director, AI & Machine Learning
Tasks
- Align AI initiatives with data platform
- Build and lead AI engineering team
- Collaborate with data engineering teams
- Communicate AI value risks and capabilities
- Define AI architecture using Databricks
- Define RPA strategy with Power Automate
- Deploy MLflow models
- Deploy conversational AI integrations
- Design automation workflows
- Design multi-agent AI frameworks
- Embed AI outputs into analytics insights
- Ensure responsible AI governance
- Establish AI development best practices
- Establish automation governance monitoring reliability
- Establish generative AI standards
- Identify AI and automation opportunities
- Implement evaluation frameworks
- Implement generative AI and agentic systems
- Implement model serving
- Implement retrieval-augmented generation
- Implement vector search
- Integrate AI models into automation workflows
- Lead enterprise AI strategy
- Lead robotic process automation function
- Maintain transparency and auditability
- Oversee AI automation design development testing deployment
- Translate business needs into AI solutions
Perks/Benefits
- N/A
Skills/Tech-stack
Agent systems | Agentic AI | Artificial Intelligence | Conversational AI | Data Governance | Databricks | Databricks Genie | Embeddings | Enterprise Data | Enterprise Data Governance | Generative AI | Intelligent Automation | Lifecycle Management | MLflow | Machine Learning | Microsoft Copilot | Microsoft Power | Microsoft Power Automate | Model Lifecycle | Model Lifecycle Management | Model Serving | Multi-Agent | Multi-Agent Systems | Power Automate | Process Automation | Retrieval-Augmented Generation | Robotic Process | Robotic Process Automation | Security Compliance | Vector Databases | Vector Search
Education
Roles
AI | AI Engineer | Architect | Automation Architect | Director | Engineer | Learning Engineer | Machine Learning Engineer
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