AI Native Engineer

Responsibilities

• Own technical execution of the AI maturity journey up to Level 3 within assigned projects or programs
• Define and operationalize AI-driven practices across the SDLC, covering requirements, design, development, testing, documentation, and delivery
• Ensure practical, repeatable, and accessible AI solutions for all delivery roles, including Engineers, QAs, Scrum Masters, and Product Owners
• Continuously assess SDLC workflows for bottlenecks and introduce AI-powered improvements with measurable impact
• Select, configure, and maintain AI tools and assistants supporting both coding activities (code discovery, reverse engineering, automated generation, refactoring, code reviews, quality analysis, technical debt identification) and non-coding activities (requirements analysis, user story mapping, technical documentation,…
• Integrate AI assistants with delivery platforms such as Azure DevOps, CI/CD pipelines, and diagramming tools
• Define and maintain agentic enablement architecture, including skills, subagents, rules, tech guides, and inter-agent contracts, and design coordinated agent workflows for story intake, coding, testing, and documentation
• Establish confidence thresholds, fallback strategies, and validation stages for AI-assisted workflows
• Develop and maintain usage guidelines, artifact change logs (skills, agents, guides), evaluation and experiment results, component-level technical documentation, and contribute to documentation for system design, AI-enabled workflows, and tooling standards
• Coach and support delivery roles in the effective use of AI tools, drive adoption to improve speed, quality, and consistency, and monitor usage patterns to identify gaps or misuse and propose solutions

Languages