- Experience in integrating AI across the Software Development Life Cycle (SDLC) including solution design, code generation, bug fixing, unit/integration testing, and technical documentation

- Hands-on experience using GitHub Copilot (Chat, Inline, Agents) or similar AI-assisted development tools, with the ability to review, refine, and productionize AI-generated outputs

- Strong solution and architecture design skills, leveraging AI for architecture exploration, API design, and creation of design artifacts

- Proven experience in authoring technical product specifications, functional and non-functional requirements, and API contracts using AI as a productivity accelerator

- Proficiency in prompt engineering for design, coding, debugging, refactoring, and documentation

- Ability to apply strong engineering judgment and accountability while using AI, ensuring security, performance, maintainability, and high code quality

- Experience designing and implementing AI-driven solutions throughout the SDLC

- Ability to use AI tools to enhance code quality and development efficiency

- Experience creating and maintaining comprehensive technical documentation with AI assistance

- Strong collaboration skills to work with cross-functional teams for defining and refining API architectures and contracts

- Adherence to software engineering best practices, especially in security and maintainability

- Knowledge of AI agents and agentic workflows is desirable

- Exposure to MCP servers or similar context-sharing mechanisms connecting repositories, APIs, and documentation to AI tools is a plus

- Basic applied understanding of AI/LLM concepts, limitations, and risks

- Practical experience using AI for intelligent automation and advanced problem solving beyond standard coding assistance