Staff Software Engineer, AI for Developer Productivity

About the role

We are seeking a highly skilled Staff Software Engineer to join the Virtualization & Embedded Software Development Tools organization.

Responsibilities

• Define the technical vision for AI-powered developer productivity capabilities across engineering tools and workflows
• Design, develop, and deliver AI-powered solutions that reduce manual effort, accelerate issue resolution, and improve software quality across development, debugging, test analysis, issue triage, documentation, and engineering support workflows
• Partner with cross-functional teams to identify high-value AI use cases and translate them into scalable products, platforms, and reusable capabilities
• Integrate AI-powered capabilities into engineering tools, workflows, and automation platforms in ways that improve reliability, usability, and adoption
• Drive productionization of AI capabilities within GM engineering environments, including cloud-hosted services, internal platforms, CI/CD systems, and developer tools
• Establish technical standards and best practices for responsible use of AI in engineering tools, including quality, traceability, maintainability, and cybersecurity considerations
• Serve as a subject matter expert and technical leader across organizational boundaries, influencing roadmaps, solution direction, and implementation priorities
• Mentor engineers on AI system design, prompt and workflow design, evaluation strategies, and toolchain integration without formal people-leader responsibility
• Present strategy, progress, recommendations, and demonstrations to technical leaders and partner organizations

Requirements

• Bachelor’s degree in Computer Science, Software Engineering, Electrical Engineering, Computer Engineering, or a related technical field
• 10+ years of experience in software engineering, developer tooling, platform engineering, machine learning engineering, applied AI, or a closely related field
• Strong expertise building and shipping production software systems, with proficiency in Python and at least one additional language used in engineering tooling environments
• Demonstrated expertise applying AI and LLM-based approaches to engineering problems such as code analysis, workflow automation, knowledge retrieval, summarization, troubleshooting, or developer productivity support
• Strong understanding of software engineering fundamentals, system design, APIs, data flows, observability, and production operations
• Experience integrating AI-powered capabilities into enterprise platforms, engineering tools, or CI/CD systems
• Experience with cloud services, containerization, and orchestration technologies
• Strong knowledge of secure engineering practices and responsible AI guardrails
• Excellent communication skills and the ability to influence technical direction across teams without formal authority
• Experience with developer platforms, build systems, testing systems, or internal engineering tools
• Experience balancing fast experimentation with production reliability, maintainability, and compliance

Qualifications

• Master’s degree or PhD in Computer Science, Software Engineering, Machine Learning, AI, or a related field
• Experience in embedded software development, automotive software, systems engineering, or safety-related toolchains
• Familiarity with GM engineering tools, engineering workflows, or internal platform environments
• Experience building AI assistants, coding agents, or domain-specific AI capabilities for engineers
• Experience with knowledge systems, vector search, ranking, workflow orchestration, or code intelligence platforms
• Experience supporting large engineering communities through reusable tools, templates, and automation
• Experience evaluating AI quality in production systems using measurable outcomes such as acceptance rate, time saved, precision and recall, hallucination reduction, or workflow completion rate
• Experience designing retrieval-augmented or tool-using AI workflows
• Experience integrating AI into GitHub-based engineering workflows or related enterprise automation pipelines