VP, AI Software Engineering (Hybrid - Flexible Options)
Tasks
- Advise leadership on AI for quality and productivity
- Build and mentor engineering teams
- Collaborate with engineering and product stakeholders
- Define AI software engineering strategy
- Define and track KPIs for AI quality initiatives
- Develop AI powered quality engineering solutions
- Drive AI model development testing deployment monitoring
- Establish AI governance risk and compliance
- Implement CI CD and platform automation
- Lead test automation and quality validation
Perks/Benefits
Skills/Tech-stack
APIs | Artificial Intelligence | CI/CD | Cause analysis | Cloud Platforms | Continuous Delivery | Continuous integration | Data Integrity | Defect prediction | DevOps | Development Lifecycle | Distributed Systems | Enterprise Architecture | MLOps | Machine Learning | Model Governance | NLP | Observability | Predictive Analytics | Privacy | Quality Assurance | Regulatory Compliance | Root Cause Analysis | Root cause | Security | Software Development Lifecycle | Software development | Test automation
Education
Bachelor of Engineering | Bachelor of Science | Master of Science | PhD
Roles
AI Software Engineer | Engineer | Software Engineer | VP | VP AI Software Engineer
Regions
Countries
States
Cities
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