Job Title: AI Productivity & Engineering Excellence Champion
Role Overview
Hands-on technical leader driving adoption of AI-powered practices to improve developer productivity, code quality, and delivery efficiency. Actively contributes to production code and applies AI in real development scenarios.
Key Responsibilities
- Hands-on Development: Build and deliver features using AI-assisted coding, debugging, and refactoring.
- AI Enablement: Introduce and scale AI tools and workflows across the SDLC.
- Code Quality: Enhance code reviews using AI; reduce defects and technical debt.
- Test Automation: Leverage AI for test generation, coverage improvement, and reliability.
- Continuous Improvement: Drive incremental refactoring and maintainability.
- Metrics: Track and improve KPIs (lead time, defect rate, code quality).
- Coaching: Mentor teams and promote best practices in AI-assisted development.
Stakeholders
Development Teams, Tech Leads, Architects, Scrum Master, Product Owner
Required Skills
Technical
- Strong hands-on experience in Java + Angular (full-stack development)
- Solid experience with Spring Boot, REST APIs, and modern frontend frameworks
- Expertise in CI/CD, Git, automated testing, and code reviews
- Good understanding of architecture, scalability, and maintainability
- Practical experience with AI-assisted development tools (Java, Angular, Full-Stack Development, Anthropic Claude, Claude Skills, GitHub Copilot, Windsurf, and Cursor AI)
Soft Skills
- Leadership by example
- Strong communication and coaching ability
- Pragmatic, problem-solving mindset
Mindset
- Product and value-driven
- Quality-focused
- Continuous improvement and experimentation mindset
Success Criteria
- Improved developer productivity and faster delivery
- Reduced defects and better code quality
- Strong adoption of AI-assisted engineering practices
- Visible impact through hands-on contributions