Sr. Staff Engineer – AI Enablement & Engineering Excellence - Hybrid

Sr. Staff Engineer – AI Enablement & Engineering Excellence

We are looking for a Sr. Staff Engineer to define how AI changes the way our engineering organization builds software. This is a hands‑on technical leadership role for someone with deep expertise in AI‑assisted development who knows how to scale it responsibly across a large engineering org and who can strengthen the engineering foundation required to do it well.

• Own the org‑wide strategy for AI in the software development lifecycle: where to apply it, how to evaluate it, and how to scale what works.
• Pilot and operationalize AI tooling across the SDLC, including AI pair programming, LLM‑assisted code review, automated test generation, intelligent observability, and agentic development workflows.
• Define adoption frameworks that account for productivity, code quality, security, cost, and responsible use, not just rollout logistics.
• Establish metrics that measure AI's actual impact on engineering velocity, quality, and developer experience, and report findings to engineering leadership.
• Bring well‑reasoned tooling recommendations to engineering leadership, not just a summary of what exists in the market.
• Align engineering AI adoption with the broader organizational AI journey, including approved vendors, enterprise policies, and coordination with Security and Legal.

• Provide architectural guidance for engineering teams building systems that integrate LLMs, AI agents, or ML models into production software.
• Define engineering standards for AI‑integrated development tooling: prompt engineering practices, evaluation frameworks, latency and cost tradeoffs, and observability for AI tools where outputs may vary.
• Work hands‑on with engineers on hard problems, including reviewing AI‑integrated system designs, writing reference implementations, and unblocking adoption at the code level.

• Identify and close the engineering gaps that slow AI adoption: insufficient test coverage, brittle CI/CD pipelines, poor observability, and unclear code ownership.
• Define and strengthen the engineering standards that make AI tooling more effective, treating this as a prerequisite to scaling AI well rather than a separate initiative.
• Drive architectural consistency across teams, so AI‑generated code and AI‑assisted workflows do not introduce new forms of technical debt.

• Serve as the primary technical authority on AI‑assisted development across the engineering organization.
• Partner with engineering leads to embed AI practices into team workflows, onboarding, and code review culture as a sustained capability, not a one‑time workshop.
• Influence engineering roadmaps and toolchain decisions at the director and VP level through clear, evidence‑based technical recommendations.
• Produce internal technical references (ADRs, integration guides, evaluation scorecards) that teams can act on independently.

• 10+ years of software engineering experience, with 3+ years focused on AI/ML tooling, LLM integration, or AI‑assisted development workflows.
• Hands‑on, production‑level experience with AI developer tools such as Git Hub Copilot, Cursor, or LLM‑powered code review and test generation.
• Deep understanding of LLM fundamentals: prompt engineering, context management, fine‑tuning tradeoffs, and evaluation of AI tools used in the development workflow.
• Experience designing and shipping AI‑integrated systems at scale, with a clear understanding of cost, latency, and quality tradeoffs.
• Demonstrated ability to drive technical adoption across large engineering organizations without direct authority.
• Strong written and verbal communication skills with the ability to make AI technical tradeoffs legible to both engineers and senior leaders.

• Prior experience in a principal or staff‑level IC role with cross‑org scope.
• Experience building internal AI enablement programs, developer experience platforms, or AI governance frameworks.
• Contributions to AI/ML open‑source projects or technical writing on AI engineering topics.
• Background in platform…