We’re looking for a Lead, AI Engineering & SDLC Automation (Director) to define and lead PSD’s AI-enabled engineering automation strategy, roadmap, and delivery function. This role will lead a team responsible for delivering AI-assisted engineering capabilities, agentic workflow automation, and SDLC automation that meaningfully improve developer productivity and software delivery across the Productivity Solutions Division.

You will own the selection, integration, governance, and adoption of AI-enabled engineering tools and automation within developer workflows, partnering across DevSecOps, Developer Experience, Security, QE, IT, and engineering teams to scale safe, reliable, and measurable AI-enabled software delivery practices.

• Lead and develop the AI Engineering & Automation team responsible for AI-assisted SDLC automation, developer workflow integration, and engineering productivity tooling.

• Define team priorities, resource needs, operating cadence, performance expectations, and execution plans.

• Own the roadmap for AI-enabled engineering automation across PSD, from tool selection and integration to adoption, measurement, and continuous improvement.

• Deliver AI-assisted engineering tools, agentic workflows, copilots, and workflow automation with measurable productivity uplift.

• Integrate AI automation into CI/CD pipelines, developer paved roads, engineering workflows, and platform services.

• Establish governance, safety guardrails, evaluation criteria, usage standards, and secure integration patterns for responsible AI adoption in engineering workflows.

• Partner with DevSecOps, Developer Experience, Security, QE, IT, and engineering teams to embed automation into software delivery practices.

• Prioritize AI automation investments based on productivity uplift, developer experience, quality, reliability, security, cost, and platform strategy.

• Drive cross-organization adoption through enablement, documentation, training, feedback loops, and measurable adoption plans.

• Resolve conflicting priorities across engineering productivity, security, reliability, cost, and responsible AI adoption.

• Define and track success measures for AI-enabled engineering automation, including productivity, adoption, toil reduction, quality, reliability, and developer experience.

What You Bring

• Typically 5+ years of experience formally or informally leading people, projects, and/or programs.

• Bachelor’s or Master’s degree or equivalent experience.

• Strong background in AI-enabled engineering, platform engineering, DevOps, developer productivity, workflow automation, or SDLC automation.

• Experience leading teams, programs, or cross-functional initiatives in complex software engineering environments.

• Experience translating organizational strategy into roadmaps, execution plans, governance models, and measurable outcomes.

• Experience with AI agents, copilots, AI-assisted software engineering tools, ML-driven automation, or agentic workflow automation.

• Strong understanding of CI/CD, SDLC tooling, developer workflows, engineering productivity tooling, and secure integration patterns.

• Understanding of responsible AI adoption, AI governance, usage controls, safety guardrails, and secure deployment patterns.

• Ability to influence senior stakeholders across engineering, product, security, QE, IT, and platform organizations.

• Experience driving adoption, enablement, and behavior change across distributed engineering teams.

• Ability to balance speed, productivity, quality, reliability, security, cost, and responsible AI use.

• Strong analytical and communication skills, with the ability to translate productivity and adoption insights into practical roadmap decisions.