Senior Director, AI Transformation and Developer Experience

Sr. Director, AI Transformation and Developer Experience

About Wind River

Wind River is a global leader in delivering software for mission-critical intelligent systems. For more than four decades, the company has been an innovator and pioneer, powering billions of systems that require the highest levels of security, safety, and reliability.

Wind River helps customers across automotive, aerospace, defense, industrial, medical, and telecommunications industries solve complex technology challenges on their journey toward the new intelligent machine economy. The company's software powers generation after generation of the safest, most secure systems in the world. Examples include playing a key role in NASA space missions such as Artemis I, the James Webb Space Telescope, and multiple Mars rovers. We've achieved recent 5G milestones including the world's first successful 5G data session with Verizon and building one of the largest Open RAN networks in the world with Vodafone.

The company has received industry recognition for its technology innovation and leadership, and for its workplace culture, including global Great Place to Work certification and being named a "Top Workplace" for ten consecutive years.

About the Role

The Sr. Director, AI Transformation and Developer Experience is the operational owner of Wind River's AI-first engineering ambition — a senior leadership role inside the engineering organization, accountable for transforming how Wind River's 1000+ engineers design, build, test, ship, and operate software. You will architect and lead Wind River's AI Engineering Center of Excellence, driving the rollout of agentic systems and AI-augmented workflows that re-engineer the software development lifecycle and step-change engineering velocity across every product line.

This is not a theoretical role. You will translate AI capability into measurable engineering outcomes — compressing release cycles, lifting developer productivity, raising code quality, and accelerating time-to-customer for VxWorks, Wind River Linux, Wind River Studio, and our cloud-native platforms. You will be the senior leader driving AI transformation inside engineering — chairing the engineering AI Steering Committee, partnering with engineering leadership across product groups, and driving buy-vs-build decisions across the foundation-model and developer-tooling landscape.

How you will contribute

• Own the engineering AI transformation roadmap and lead the AI Engineering Center of Excellence.
• Define and execute Wind River's multi-year strategy for AI platforms, agentic capabilities, and developer tooling across the engineering organization — directly aligned with engineering velocity, quality, and time-to-customer targets. Chair the engineering AI Steering Committee that drives prioritization and investment with engineering leadership, and serve as the senior sponsor and internal thought leader who reinforces Wind River's position in the intelligent-systems era.
• Architect and drive the rollout of agentic systems for engineering operations.
• Partner with engineering operations leaders to re-engineer high-volume, high-friction workflows — build/release pipelines, CI/CD, test orchestration, defect triage, code review, on-call/incident response, telemetry analysis, and release management — into autonomous, self-driving systems that compress cycle time and lift throughput across 1000+ engineers.
• Lead the AI transformation of the software development lifecycle.
• Set the strategy for integrating AI into requirements, design, code, review, test, debug, and release — across product engineering, platform/infra, QA, DevOps/SRE, and release engineering — so AI becomes a permanent, measurable layer in how we ship. Partner with engineering leaders across product groups to drive hyper-automation and step-change improvements in developer productivity, code quality, and time-to-market for our embedded and cloud-native portfolios.
• Define and steward Wind River's Developer Experience Operating System.
• Define the standardized, opinionated AI-native operating model for the engineering organization — curated coding assistants (Claude Code, Codex, Copilot), agent runtimes, eval harnesses, prompt-as-code repositories, golden-path workflows, and observability — so 1000+ engineers solve the same problem the same way. Codify emerging AI best practices into shared primitives that eliminate per-team improvisation, close coverage gaps, and reduce friction across the SDLC.
• Set the strategy for token economics and the model portfolio.
• Establish unit economics on every AI engineering workflow — cost-per-task, model selection, intelligent routing, caching, fine-tuning vs. prompting, and inference-tier strategy — and drive buy-vs-build decisions across foundation models, hosting