Engineering Manager, Observability

Engineering Manager

This role is based remotely 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 three times a week, at minimum.

The AI Cloud and Developer Infrastructure organization is responsible for delivering and maintaining the tools and services engineers here at GM use every day to do their best work and drive our cars forward. Tools and services we work on enhancing the entire development process of engineers at GMhow / where code is checked out, modified, compiled, tested, merged, and eventually deployed. Our goal is to ensure our AV engineers and others here have world-class tools and a seamless development experience so that they can focus on the problems that matter most in their domain.

We are looking for an Engineering Manager with a deep technical background, experience building and running engineering teams, and who is passionate about developer productivity. As a leader on this team, we are looking for someone who cares deeply about the technical development of engineers on and off the team and can effectively balance the needs and priorities of the business, our users, and the growth of our engineers. This leader will start delivering impact through observability frameworks and will evolve depending on business needs, but they will be expected to identify high ROI investments with minimal guidance.

What You'll Do (Responsibilities)

Team leadership : Manage and grow a team of engineers, conducting performance reviews, providing coaching, and supporting career development.

Technical strategy : Define and execute the technical vision and roadmap for the observability platform, ensuring it provides actionable insights into complex systems.

Architectural oversight : Provide technical guidance on instrumentation, logging, metrics, and tracing to ensure comprehensive visibility across GM's AV software stack.

Incident response : Ensure the team's tools enable rapid detection, debugging, and resolution of unknown or unforeseen system failures to minimize downtime.

Cross-functional collaboration : Work with other engineering teamssuch as those developing AI / ML, firmware, and infrastructureto implement observability practices and improve system reliability.

Platform development : Lead the development of internal tools and data pipelines to collect, analyze, and visualize telemetry data at a massive scale.

Vendor management : Manage relationships and costs associated with third-party observability software and platforms.

Minimum Qualifications (Must-Have)

Leadership experience : 5+ years of experience leading software or site reliability engineering (SRE) teams and balancing the tradeoff between velocity and reliability.

Bachelors Degree in Computer Science or related field or equivalent work experience.

Observability expertise : Deep understanding of core observability pillars : logs, metrics, and traces. Experience with technologies like Prometheus, Grafana, OpenTelemetry, and log management systems is crucial.

Software architecture : Strong background in designing, developing, and architecting distributed systems, cloud-native applications, and microservices.

Programming proficiency : Familiarity with Go, Python, Typescript or similar along with software development practices to inform code reviews and architectural decisions.

Cloud infrastructure : Experience with modern cloud offerings like GCP, AWS, or Azure and technologies like CI / CD pipelines, Kubernetes, and Docker.

Communication skills : Excellent interpersonal and communication skills to collaborate effectively with diverse teams and stakeholders.

Preferred Qualifications (Nice-to-Have)

Management experience : 3+ years of experience managing software engineering or site reliability engineering (SRE) teams.

Experience working with GCP, AWS, or Azure.

Familiarity with Kubernetes, Docker, Istio, Terraform, Prometheus, Grafana, TSDBs, and observability pipelines (e.g. either for logging or metrics or tracing).

Skilled in defining and instrumenting SLIs and SLOs.

Own or contribute to Open Source projects.

Passion for self-driving technology and its potential impact on the world.

Compensation

The compensation information is a good faith estimate only. It is based on what a successful applicant might be paid in accordance with applicable state laws. The compensation may not be representative for positions located outside of New York, Colorado, California, or Washington.

The salary range for this role is $200,000 to $285,000. The actual base salary a successful candidate will be offered within this range will vary based on factors relevant to the position.

Bonus Potential : An incentive pay program offers payouts based on company performance, job level, and individual performance.

Benefits : GM offers a variety of health and wellbeing benefit programs. Benefit options include medical, dental, vision, Health Savings Account, Flexible Spending Accounts, retirement savings plan, sickness and accident benefits, life insurance, paid vacation & holidays, tuition assistance programs, employee assistance program, GM vehicle discounts and more. Company Vehicle : Upon successful completion of a motor vehicle report review, you will be eligible to participate in a company vehicle evaluation program, through which you will be assigned a General Motors vehicle to drive and evaluate. Note : program participants are required to purchase / lease a qualifying GM vehicle every four years unless one of a limited number of exceptions applies.

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We encourage interested candidates to review the key responsibilities and qualifications for each role and apply for any positions that match their skills and capabilities. Applicants in the recruitment process may be required, where applicable, to successfully complete a role-related assessment(s) and / or a pre-employment screening prior to beginning employment. To learn more, visit How we Hire.

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