What you'll be doing

• Build the current-state picture by discovering how software is built across diverse code-producing teams.
• Define SDLC archetypes by condensing team mappings into a verified map and grouping similar delivery requirements.
• Describe target AI-native workflows for each archetype, specifying where AI-assisted development, agents, and automated checks fit.
• Own the capability backlog by translating gaps into prioritized platform capabilities with clear requirements and acceptance criteria.
• Maintain communication channels between distributed development and research teams and the Architecture group to gather and triage needs.
• Validate and steer new capabilities by piloting, gathering feedback, measuring outcomes, and refining priorities and archetypes.

Requirements

• First-hand experience with the full software development lifecycle and its variation across different teams.
• Ability to structure highly ambiguous and complex technical environments.
• Working knowledge of AI-native software development concepts, including spec-driven development, agent harnesses, verification design, autonomy tiers, and policy-as-code.
• Experience owning requirements and priorities for platform and enterprise tooling from discovery through acceptance.
• Outcome-oriented mindset focused on team metrics such as cycle time, quality, and adoption to guide priorities.
• Strong, adaptable technical communicator who can build trust with development and research teams and guide senior stakeholder decisions.