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

GEICO • Palo Alto, CA

8h • Hybrid

About The Position

At GEICO, we offer a rewarding career where your ambitions are met with endless possibilities. Every day we honor our iconic brand by offering quality coverage to millions of customers and being there when they need us most. We thrive through relentless innovation to exceed our customers’ expectations while making a real impact for our company through our shared purpose. When you join our company, we want you to feel valued, supported and proud to work here. That’s why we offer The GEICO Pledge: Great Company, Great Culture, Great Rewards and Great Careers. 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. You will own our AI adoption strategy end-to-end: evaluating and selecting tooling, designing integration patterns, building internal playbooks, and working directly with engineers to embed AI into the development lifecycle in ways that produce real, measurable outcomes. Engineering excellence (standards, architecture, process) is the platform you will build to make that adoption stick.

Requirements

• 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 GitHub 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.

Nice To Haves

• 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 engineering or developer tooling with an AI focus.

Responsibilities

• 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.

Benefits

• Market-competitive compensation
• 401K savings plan vested from day one that offers a 6% match
• Performance and recognition-based incentives
• Tuition assistance
• Mental healthcare
• Fertility assistance
• Adoption assistance
• Workplace flexibility
• GEICO Flex program (ability to work from anywhere in the US for up to four weeks per year)

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed