• Build and deploy custom model context protocol (MCP) connectors for new and existing services • Design and implement custom agentic workflows using cloud AI platforms • Develop server-side application logic and APIs that integrate AI capabilities with existing enterprise systems • Contribute to the development and maintenance of reusable AI component libraries and shared code infrastructure • Write high-quality code, applying best practices, coding standards, and design patterns for AI systems • Participate in the entire AI solution lifecycle, including requirement gathering, design, development, testing, and deployment, using an agile, iterative process • Participate in code reviews and ensure code quality through effective testing strategies and security validation • Collaborate with infrastructure teams, security teams, developers, designers, testers, project managers, product managers, and project sponsors • Communicate tasking estimation and progress regularly to a development lead and product owner through appropriate tools • Ensure seamless integration with backend systems, cloud services, databases and messaging systems • Team with other developers, fostering a culture of continuous learning and professional growth in AI engineering