Software Engineering Manager - Order Fulfillment Software Factory

General Motors•Austin, TX

4d•Hybrid

About The Position

The Order Fulfillment Software Factory delivers GM’s end-to-end software for two value streams: Source to Deliver (purchasing, supplier management, supply chain, and logistics) and Order to Deliver (vehicle sales, configuration, scheduling, and delivery). The factory is advancing GM’s SaaS First, Cloud First, and AI First direction, working closely with various business units and peer software factories. We are seeking a Software Engineering Manager who codes to lead a team of approximately 6–12 engineers. This role is a player-coach position, requiring 30–40% hands-on coding, system design, prototyping, and daily interaction with AI coding agents. The manager will be the team's technical anchor, responsible for scoping problems, designing systems, shipping code, and making agentic AI the default for the team's development processes. The role involves setting technical direction, ensuring delivery and quality, and fostering team growth.

Requirements

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.
At least 1 year of daily hands-on use of AI coding assistants or agents in real development work, with concrete examples.
Experience with cloud platforms such as Azure, AWS, or GCP.
Experience with APIs and microservices.
Experience with modern CI/CD, code review, and source control practices.

Nice To Haves

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.
Experience 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.

Responsibilities

Lead the team's delivery and direction by translating factory strategy into clear objectives and operating plans.
Manage team resources, delegate work, and reprioritize based on changing business needs.
Own team metrics and KPIs, including delivery, quality, reliability, and business outcomes.
Drive strategy and implementation for large projects impacting multiple departments and business partners.
Align technical initiatives with key business objectives and contribute to the technology roadmap.
Handle competing demands, sensitive situations, and conflicts within the team and with stakeholders.
Be accountable for workforce planning and operational/financial decisions, including cloud and AI tooling spend.
Act as the technical lead, writing, reviewing, and merging production code for critical features, defects, and proofs of concept.
Design software systems and define architecture for team projects, including services, APIs, integrations, and data models.
Participate in architecture reviews across the factory.
Guide engineers in problem-solving and solution development.
Propose new technologies to improve business operations, product experience, quality, and time to market.
Own operational excellence, including on-call participation, incident response, postmortems, and delivering high-quality work on schedule.
Make AI coding agents part of everyday work across planning, implementation, testing, code review, refactoring, documentation, and operations.
Build and maintain the team’s AI agent setup, including instructions, prompts, tool integrations, and CI pipelines.
Set guardrails for AI-generated code to ensure safety and quality, including test coverage, human review standards, and data handling.
Use agents to modernize legacy systems, such as generating test harnesses and running automated migrations.
Track the impact of AI adoption through metrics like cycle time and defect escape rate.
Hire engineers and make staffing decisions to build the right talent mix.
Conduct one-on-ones and career conversations, planning resources for engineer growth.
Manage performance, including goal setting, feedback, calibration, and addressing underperformance.
Coach engineers on directing, verifying, and owning AI-generated work.
Champion change management for agentic development and role-model GM's Behaviors.