Job Description

The Order Fulfillment Software Factory delivers GM’s end-to-end software for two value streams. Source to Deliver covers purchasing, supplier management, supply chain, and logistics. Order to Deliver covers how GM sells, configures, schedules, and delivers vehicles to dealers and customers. The factory is advancing GM’s SaaS First, Cloud First, and AI First direction. It works closely with GPSC Business Area IT, Sales and Marketing Business IT, and GM’s peer software engineering, mainframe, and SAP factories to deliver consistent, modern solutions at speed.

We’re looking for a Software Engineering Manager who codes. You’ll lead a team of approximately 6–12 engineers with a mix of skills, sometimes including a technical lead or first-line lead, that owns a product or service area such as Vehicle Order Management, Order Scheduling, or Global Logistics. You’ll be the team’s technical anchor: scoping complex problems, designing systems, and shipping alongside your engineers. You’ll also make agentic AI coding the default way your team builds, tests, and operates software.

This is a player-coach role. We expect you to spend approximately 30–40% of your time hands-on, including writing and reviewing production code, designing systems, prototyping, and working daily with AI coding agents. You’ll set your team’s technical direction and be accountable for its delivery, quality, and growth.

• Turn the factory’s strategy into clear direction, objectives, and operating plans for your team. Allocate resources, delegate work, and reprioritize as business needs change.
• Own your team’s metrics and KPIs, including delivery, quality, reliability, and business outcomes, and make measurable contributions to the factory’s goals.
• Drive strategy and implementation for large projects that affect multiple departments and business partners, including GPSC, dealers, and suppliers.
• Tie technical initiatives to key business objectives and begin building your area’s technology roadmap with Product Management.
• Handle competing demands, sensitive situations, and conflicts within the team and with other teams. Build alignment with stakeholders who are skeptical of new approaches.
• Be accountable for workforce planning and operational and financial decisions in your area, including cloud and AI tooling spend.

• Act as the technical lead for your team’s workstream. Write, review, and merge production code for critical-path features, complex defects, and proofs of concept.
• Design software systems and define architecture for team-level projects, including services, APIs, event-driven integrations, data models, and SaaS/ERP integrations. Participate in architecture reviews across the factory.
• Guide engineers as they scope complex problems and develop creative, pragmatic solutions. Be the team’s go-to resource for technology, cross-team interfaces, and company policies and processes.
• Propose new technology that changes how the business works, with forward-looking impact on product experience, quality, and time to market.
• Own operational excellence. Participate in on-call, lead incident response and postmortems, and deliver high-quality work on schedule, with quality as the priority.

• Make AI coding agents, such as Claude Code, GitHub Copilot agent mode, and Cursor, part of everyday work across planning, implementation, testing, code review, refactoring and migrations, documentation, and operations.
• Build and maintain the team’s agent setup, including repository-level agent instruction and context files, reusable prompts and skills, MCP and other tool integrations with internal systems, and CI pipelines that run agents for automated pull-request review, test generation, and dependency upgrades.
• Set guardrails so agent-generated code is safe to ship, including test coverage and evaluation checks, human-review standards, sandboxing and permissions, secret and data handling, and provenance checks.
• Use agents to modernize legacy order and supply chain systems faster, for example by generating test harnesses for legacy code, running automated migrations, and documenting undocumented systems.
• Track impact through measures such as cycle time, change-failure rate, defect escape rate, and developer experience. Share what works with peer teams and help establish factory-wide practices.

• Hire engineers and make internal and external staffing decisions to build the right mix of talent and experience.
• Hold regular one-on-ones and career conversations. Plan people resources so engineers continue to grow, and assign work that plays to each person’s strengths.
• Run performance management, including goal setting, feedback, calibration, and addressing underperformance. Apply company policies consistently and fairly.
• Coach engineers to direct, verify, and own AI-generated work, and to maintain a high bar for everything they merge.
• Champion change management as the team adopts agentic development. Role-model GM’s Behaviors while making room for individuality and diverse perspectives.

• Bachelor of Science or Bachelor of Applied Science in Computer Science, Computer Engineering, Mathematics, Information Technology, Information Security, Cybersecurity, or a related field plus 6–9 years of relevant experience; or 10–12 years of full-time relevant experience.
• At least 2 years of experience managing a team of software engineers with varied skill levels, including hiring, coaching, and performance management.
• At least 3 years of experience designing and architecting new and existing systems for reliability and scale.
• Current, hands-on coding proficiency in one or more of Java, Python, TypeScript/JavaScript, Go, C#, or Kotlin. Candidates will be asked to code during the interview process.
• At least 1 year of daily hands-on use of AI coding assistants or agents in real development work, with concrete examples of what worked, what did not, and why.
• Experience with cloud platforms such as Azure, AWS, or GCP; APIs and microservices; and modern CI/CD, code review, and source control practices.

• At least 3 years of engineering management experience, or experience leading a team that included other leads.
• Domain experience in order management, supply chain, procurement, logistics, dealer or retail systems, or e-commerce fulfillment.
• Experience integrating with SaaS and ERP platforms, such as SAP or Salesforce, and with event streaming and messaging technologies, such as Kafka.
• Experience modernizing legacy or mainframe systems into cloud-native services.
• Experience building on LLM APIs and agent tooling, including tool or function calling, Model Context Protocol (MCP), prompt and context engineering, and evaluation harnesses.
• Experience with Agile or SAFe delivery, including PI planning and working across Agile Release Trains.
• Master’s degree in Computer Science or a related field.