Director of AI Engineering
Tasks
- Build AI engineering and platform organizations
- Build AI technology strategy
- Define AI adoption roadmaps
- Define AI governance standards and guardrails
- Design internal controls for AI risk mitigation
- Drive enterprise adoption and change management
- Embed AI into SDLC workflows
- Embed risk security compliance controls
- Establish AI adoption and SDLC impact metrics
- Establish AI operating model
- Implement maturity based adoption models
- Integrate LLM patterns
- Lead enterprise AI platform capabilities
- Lead vendor evaluations
- Maintain audit readiness and remediation
- Manage AI delivery roadmaps and metrics
- Manage vendor and product relationships
- Onboard models and tools
- Optimize AI platform cost and utilization
- Oversee engineering delivery execution
- Provide people leadership and culture
- Standardize repositories and CI CD pipelines
Perks/Benefits
- N/A
Skills/Tech-stack
Artificial Intelligence | Audit Readiness | CI/CD | Compliance | Data-Driven Decision Making | Data-driven | Decision Making | DevOps | Developer experience | Development Life Cycle | Generative AI | Governance | KPI | Language Models | Large Language Models | Machine Learning | OKR | Project Management | Quality Engineering | Repository Management | Risk Management | Software Development Life Cycle | Software Security | Software development
Education
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