Staff Engineer

Location

• This role is remote, but if you live within a 50‑mile radius of Austin, Detroit, Warren, Milford, Mountain View, or Sunnyvale, you are expected to report to that location at least three times a week.

About

The AI Cloud and Developer Infrastructure organization delivers and maintains the tools and services engineers at GM use daily to do their best work and drive our cars forward. We enhance the entire development process—how/where code is checked out, modified, compiled, tested, merged, and eventually deployed. Our goal is to provide AV engineers and others with world‑class tools and a seamless development experience so they can focus on the problems that matter most in their domain.

Role

We are looking for a Staff Engineer with extensive engineering experience, a strong background in developer tools and technologies, and a passion for developer productivity. As a leader on this team, you will care deeply about the technical development of other engineers, balance business needs, user priorities, and the growth of your teammates, and identify high‑ROI investments with minimal guidance.

Responsibilities

• Communicate with executive presence by presenting to leadership, initiating org‑wide programs, and building/socializing complex roadmaps decomposed into workstreams, milestones, and timelines to align stakeholders and secure buy‑in.
• Scale engineering culture and talent by running large trainings, coaching leads and ICs, defining interview loops, identifying gaps, creating coaching plans, and staffing workstreams appropriately.
• Secure delivery under pressure by driving collaboration, crisis response, conflict resolution, and stakeholder buy‑in, while mentoring teammates to land the roadmap and managing vendor relationships when relevant.
• Model and improve culture by exemplifying company values and sharing focused feedback with managers, HRBPs, and skip‑levels.
• Deliver high‑quality, exclusive solutions on expedited timelines by operating autonomously and hitting deadlines.
• Set roadmaps and workstream priorities with managers by aligning scope, sequencing, and resources.
• Restore execution health by finding gaps early and partnering with managers and L8/L7 leads to adjust, pivot, and replan roadmaps and workstreams.
• Simplify at scale by identifying and acting on opportunities to remove complexity and redundancy.
• Advance the state of the art by prototyping high‑risk ideas, tracking academia, and achieving top performance.
• Lead decisions and quality by acting as a technical authority and modeling best practices in code, testing, and documentation.
• Ship breakthroughs by opening new areas, delivering key contributions, and refining requirements with stakeholders.
• Architect and execute by setting strategy and roadmaps, breaking down work, aligning stakeholders, and managing dependencies.
• Optimize systems and teams by simplifying, cutting redundancy and tech debt, improving tooling, mentoring, and representing cross‑org dependencies.

Minimum Qualifications (Must‑Have)

• 5+ years of leadership experience in software or site reliability engineering (SRE) teams, balancing velocity and reliability.
• Bachelor’s degree in Computer Science or related field, or equivalent work experience.
• Deep understanding of core observability pillars (logs, metrics, traces) with experience in Prometheus, Grafana, OpenTelemetry, and log management systems.
• Strong background in designing, developing, and architecting distributed systems, cloud‑native applications, and microservices.
• Proficiency in Go, Python, TypeScript, or similar languages, with solid software development practices for code reviews and architectural decisions.
• Experience with modern cloud platforms (GCP, AWS, or Azure) and technologies such as CI/CD pipelines, Kubernetes, and Docker.
• Excellent interpersonal and communication skills for effective collaboration with diverse teams and stakeholders.

Preferred Qualifications (Nice‑to‑Have)

• 7+ years of experience in software engineering or SRE teams.
• Experience working with GCP, AWS, or Azure.
• Familiarity with Kubernetes, Docker, Istio, Terraform, Prometheus, Grafana, TSDBs, and observability pipelines (logging, metrics, tracing).
• Skilled in defining and instrumenting SLIs and SLOs.
• Contributions to open‑source projects.
• Passion for self‑driving technology and its potential impact on the world.

Compensation & Benefits

• Salary range: $180,000 – $235,000 (base salary within this range varies based on relevant factors).
• Bonus potential: Incentive pay program based on company performance, job level, and individual performance.
• Benefits: Medical, dental, vision, Health Savings Account, Flexible Spending Accounts, retirement savings plan, sickness and accident benefits, life insurance, paid vacation & holidays, tuition assistance, employee assistance program, GM vehicle discounts, and more.
• Company vehicle: After a successful motor vehicle report review, eligibility for a GM vehicle evaluation program (participants must purchase/lease a qualifying GM vehicle every four years unless an exception applies).