Staff Software Engineer – Developer Experience

About the role

Job Description

The Role

Hybrid: This role is categorized as hybrid. This means the successful candidate is expected to report to Austin TX IT Innovation Center or Warren Michigan GM Technical Center 3 days per week (T-W-Th)

The Role:

This Staff Software Engineer – Developer Experience role sits within the Developer Experience (DevEx) team at the intersection of DevEx, data, and business strategy. The team provides tools, platforms, metrics, and enablement programs that reduce friction for engineers, streamline software delivery workflows, and improve developer satisfaction and productivity across General Motors.

In this role, you will focus on Developer Productivity & Insights—defining how we measure and understand engineering effectiveness, partnering with platform and product teams to synthesize signals across SDLC systems, and translating those insights into clear narratives and recommendations for senior engineering leadership up to the CISO office. Rather than owning a single platform, you will drive change through influence: shaping our metrics strategy, defining and evolving golden paths, evaluating how AI is transforming developer workflows, and turning data into better tools, workflows, and outcomes for engineers.

The DevEx team exists to make life dramatically better for software engineers at GM. As a Staff Software Engineer, you’ll help lead the shift from a traditional IT model to an AI-native engineering organization—designing and building automation, golden paths, and AI-driven solutions that remove friction from developer workflows while mentoring and upskilling engineers across IT.

What you’ll do:

- Lead technical strategy and delivery for platforms, tools, and workflows that improve developer productivity, quality, and satisfaction across GM.

- Design and implement golden paths (opinionated, paved-road workflows) for shipping software—covering repo structure, CI/CD, testing, security, observability, and deployment.

- Build automation and self-service capabilities that reduce manual toil (e.g., environment provisioning, pipeline setup, guardrail enforcement, standards checks).

- Embed AI into engineering workflows, including agents and copilots that assist with planning, coding, testing, documentation, and operations.

- Partner with product, security, infra, and application teams to understand pain points and translate them into concrete platform and tooling improvements.

- Act as a multiplier and mentor across the organization, coaching engineers and providing guidance on software engineering, AI-assisted development, and recommended practices.

- Define and track outcome-focused metrics (e.g., lead time for changes, PR cycle time, change failure rate, developer satisfaction) and use data to guide investments.

- Contribute to and influence engineering standards, patterns, and reference architectures used across Core IT and beyond.