AI Native Engineer

We are seeking an AI Native Engineer to drive the technical execution of our AI maturity journey and embed AI-driven practices across the software development lifecycle. In this role, you will design, implement, and scale agentic workflows and AI tooling that empower delivery teams to ship software faster, with higher quality and consistency. You will act as both a hands-on builder and an enabler, coaching engineers, QAs, Scrum Masters, and Product Owners on the effective use of AI assistants throughout the SDLC.
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, test case generation and maintenance)
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
Track emerging AI trends relevant to the SDLC, evaluate applicability, and pilot promising approaches such as background agents, AI-enabled CI/CD workflows, and spec-driven development tools
Requirements
5+ years of software engineering experience, with a strong background in .NET
At least 1 year of relevant leadership experience
Expertise in context engineering and advanced prompt patterns, including the ability to create and maintain shared prompt libraries and reusable instruction sets
Proficiency in AI Engineering, AI Assistants, and SDLC Implementation
Hands-on experience with GitHub Copilot, Claude Code, and cloud-based AI platforms
Competency in ensuring prompt consistency and workflow reusability
Skills in integrating AI tools with SDLC systems such as Azure DevOps, CI/CD, and documentation tools
Understanding of agentic workflows, multi-agent communication, and coordinated workflows
In-depth understanding of the software development lifecycle, beyond just automation
Capability to optimize SDLC processes using AI while remaining mindful of quality, security, traceability, and auditability concerns
English language proficiency at an Upper-Intermediate level (B2) or higher
Nice to have
Familiarity with Azure DevOps, Microsoft Azure, and Python
Background in GenAI application development and GenAI application testing
Knowledge of GenAI for systems engineering productivity
Demonstrated use of GenAI for database administration productivity