Jobs at General Motors

Leads software engineering teams delivering enterprise HRIS and corporate systems across cloud, SaaS, and hybrid environments. Responsibilities include setting technical priorities, guiding architecture, modernizing applications, developing APIs and platform capabilities, improving reliability and observability, and implementing Agile, DevSecOps, CI/CD, automation, and AI-enabled solutions. The manager also oversees hiring, performance management, stakeholder collaboration, responsible AI governance, cloud migrations to Azure, and engineering culture development.

Design, develop, and architect scalable Golang software supporting enterprise data architecture. Lead technical design, collaborate across teams, mentor engineers, solve complex technical problems, and contribute to Agile delivery practices. Ensure software quality through code reviews, automated testing, CI/CD, and operational support while shaping technical roadmaps and architectural direction.

Recruits interns, co-ops, new graduates, and other early-career talent across technical and business roles. Manages requisitions through sourcing, screening, interviews, offers, and pre-employment activities; builds university and candidate pipelines; partners with hiring managers and HR; supports campus recruiting and intern conversion; maintains recruiting data in Workday and other systems; and uses metrics to improve hiring processes and candidate experience.

Design, implement, benchmark, and optimize CUDA-based GPU kernels and custom operators for on-vehicle ML inference. Build tooling for profiling and debugging, integrate kernels into the ML runtime, collaborate with compilers and architecture teams, and deliver high-performance, production-grade libraries meeting strict latency, throughput, and reliability targets.

Build and operate full-stack vehicle software integrity systems using Next.js and Go. Develop data visualizations and dashboards, extend shared component libraries, collaborate with product and design teams, and ensure code quality through testing, reviews, debugging, and performance analysis. The role requires technical ownership, architectural decision-making, cross-functional communication, mentoring, and effective delivery amid changing priorities.

Lead and execute adversary emulation and purple team operations to validate detections, logging, and response. Build repeatable MSV-based validation workflows, develop custom offensive tooling (C2, payloads, automation), test cloud and endpoint attack paths (AWS, GCP, Azure), and partner with Detection Engineering and Incident Response to convert findings into improved detections, documentation, and hunts.

Build and support authenticated owner web experiences across front-end React UIs and backend Java/Spring Boot services. Design, implement, test, and troubleshoot features and APIs, collaborate with product and design, contribute to architecture and CI/CD practices, and improve developer velocity and platform consistency.

Design and develop backend services, APIs, microservices, integrations, and event-driven solutions for digital commerce and order management. Own testing, CI/CD, deployments, observability, cloud infrastructure, and production reliability using Azure, Docker, and Kubernetes. Troubleshoot incidents, improve security and scalability, apply AI-assisted development practices, mentor engineers, participate in hiring, and communicate technical risks and decisions to stakeholders.

Designs and implements privacy-by-design controls across enterprise data platforms, analytics, AI systems, digital products, and connected vehicle technologies. Develops privacy-preserving solutions including pseudonymization, tokenization, encryption, masking, consent management, access controls, and data minimization. Partners with Engineering, Legal, Privacy, Cybersecurity, Product, and Data Governance teams to embed privacy requirements into software and vehicle development lifecycles. Supports standards, assessments, audits, control validation, remediation, and technical guidance.

Manages cradle-to-close government contracts and subcontracts for defense programs. Responsibilities include contract administration, bid and proposal support, FAR/DFARS/OTA compliance, negotiation, drafting NDAs and teaming agreements, subcontract management, change control, procurement processes, and stakeholder engagement with DoD, government agencies, customers, executives, and internal teams. The role requires strong federal contracting expertise, leadership, communication, and collaboration skills.

Design and deliver enterprise-grade AI workflow transformations on GCP. Build secure, event-driven backend services and multi-step AI agents, integrate bots with enterprise systems, implement telemetry, testing, CI/CD, HITL validation, and create reusable architecture, documentation, and runbooks while guiding adoption and governance.

Design, build, and scale AI-enabled workflow and automation solutions across collaboration platforms and enterprise systems. Translate manual processes into secure, reusable, event-driven automations using Python/JavaScript, integrate AI capabilities like Gemini, implement logging and telemetry, and partner with product, security, and business teams to deploy and sustain enterprise transformation solutions.

Build and maintain master data, metadata, repositories, logical data models, and data standards. Assemble complex datasets, improve data processes and infrastructure scalability, and develop industrialized analytical datasets and delivery mechanisms. Use data pipelines to generate insights into customer acquisition, operational efficiency, and business performance metrics. This is a hybrid role requiring three days in the office and two days remotely.

Lead AI, machine learning, and data science workstreams from methodology through production delivery. Develop scalable, maintainable analytical code, explore new methods, influence product decisions, and collaborate with engineering, product, business, and data teams. Translate technical tradeoffs into actionable recommendations, present findings to technical and business audiences, and deliver measurable business impact while managing risks and maintaining methodological quality.

Lead development of scalable, reliable continuous integration infrastructure supporting autonomous-vehicle development, machine learning training, simulation, and remote builds. Specialize in Remote Build Execution and a FUSE-based file system, enabling source-code editing and developer workflows. Design and implement productivity improvements, evaluate technologies, influence technical roadmaps, establish engineering best practices, manage technical debt, and mentor engineers while balancing business and customer priorities.

Lead architecture and development of GM’s in-vehicle AI assistant platform on Android Automotive OS. Build scalable APIs, SDKs, edge-cloud integrations, CI and automated validation infrastructure, and robust AIDL/IPC application contracts. Guide engineering execution, optimize latency and memory, integrate AI/ML evaluation pipelines, and collaborate with product and UX teams. The role requires extensive Android architecture experience, technical leadership, Kotlin and Java expertise, and familiarity with distributed client-server systems.

Leads the architecture and development of scalable backend APIs, microservices, distributed systems, data pipelines, and integrations for vehicle commerce platforms. Responsibilities include modernizing legacy systems, implementing automation, writing secure and tested code, mentoring engineers, evaluating technologies, and championing CI/CD, observability, and performance improvements. The role requires expertise in Java, Spring Boot, Kafka, cloud-native infrastructure, Azure, containers, databases, and generative AI technologies.

Lead full-lifecycle software development integrating robots and plant-floor devices with manufacturing data systems. Build, maintain, debug, optimize, and secure production applications using C++, Java, Azure, ROS, testing, CI/CD, and agile practices. Collaborate with manufacturing, controls, OT/IT, and data teams; support on-call operations, resolve urgent production issues, mentor developers, and conduct code reviews.

Lead the architecture, development, and productionization of scalable data pipelines and governed data products in Databricks. Transform heterogeneous source data for analytics, AI, and machine learning; establish data quality, observability, governance, and delivery standards; and support experimentation, model development, deployment, and monitoring. Lead cross-team initiatives, influence technical roadmaps, mentor engineers and data scientists, and develop reusable AI and multi-agent data capabilities.

Found and establish GM Vehicle Autonomy’s centralized SRE practice. Build shared reliability tooling, service catalogs, SLOs, error budgets, readiness automation, standards, and production infrastructure. Partner with service owners to assess criticality, dependencies, failure modes, and operational health. Improve incident response, post-incident practices, on-call sustainability, and toil reduction while driving adoption across infrastructure teams. The role requires strong software engineering and distributed-systems expertise across Linux, networking, Kubernetes, cloud, CI/CD, and observability.