General Motors
Sr. Systems Engineer - Manufacturing Plant Floor Systems
Austin, Texas, United States of America · Warren, Michigan, United States of America
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- Seniority
- Senior
- Country
- US
- Work mode
- On-site / unstated
- First seen by hirly
- 8 Oct 2026
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the posting
Job Description
The Role
GM's Manufacturing Plant Floor Systems is distributed between Austin, TX, and Warren, MI. We are the group within GM building innovative IT solutions supporting manufacturing, leveraging current and emerging technologies. Our focus includes technologies around error proofing, monitoring and control, robotics, AI, and intelligent automation. Our work supports GM manufacturing goals to build quality products with zero defects.
The Sr. Systems Engineer is responsible for leading the deployment, modernization, and ongoing support of software applications used globally in GM manufacturing plants. This role will help deconstruct existing deployment processes and make them AI-centric, improving speed, repeatability, reliability, and business engagement across GM’s manufacturing footprint. In this role, you will work hands-on to build full-stack application environments based on detailed requirements and system specifications. Deployment activities will include gathering requirements from manufacturing plants, updating existing software installations, configuring applications for plant-specific needs, testing and troubleshooting application or plant-configuration issues, and developing automation for repeatable deployment activities.
The ideal candidate combines deep experience with GE Digital CIMPLICITY (SCADA), OPC UA/DA, PLC-to-MES data integration, and shop-floor IT infrastructure with hands-on expertise in AI/ML integration. The role will apply generative AI to automate PLC and SCADA script generation, develop predictive maintenance analytics, and enable natural-language query interfaces for plant-floor data while preserving the reliability and operational stability required in manufacturing environments.
This role requires a strong development background to build new capabilities, process automation, test automation, and AI-enabled deployment workflows. The engineer will identify and implement responsible AI solutions, contribute to security lifecycle maintenance, ensure that third-party applications and operating systems comply with the GM IT statement of technical direction, and partner with development and support teams to maintain uptime, reliability, security, and operational readiness.
What You'll Do
- Deconstruct existing deployment processes and identify opportunities to make them user-driven, AI-centric, secure, repeatable, measurable, and scalable.
- Deploy, configure, update, and maintain control-room and plant-floor software on shop-floor IT infrastructure.
- Work closely with IT infrastructure delivery teams to install and configure virtual servers in plant data centers with minimum supervision.
- Work closely with IT Project Management to ensure launch and deployment activities are tracking for on-time delivery, escalating risks as necessary with minimum supervision.
- Identify repeatable deployment actions for automation through scripting, CI/CD pipelines, infrastructure-as-code, and AI-assisted workflows.
- Design and implement AI/ML capabilities, including generative AI for PLC/SCADA script generation, predictive maintenance analytics, and natural-language interfaces for plant-floor data.
- Establish appropriate validation, testing, human review, security, and traceability practices for AI-generated scripts, configurations, and recommendations.
- Work with in-plant resources to validate application functionality, data quality, and integration with physical systems.
- Provide analysis and site-specific business configuration required to meet launch and deployment initiatives.
- Coordinate testing with upstream and downstream plant software applications to validate data continuity and operational behavior.
- Support GE Digital CIMPLICITY, OPC UA/DA, PLC-to-MES integrations, Kepware connectivity, and related manufacturing data flows.
- Investigate IT system integration problems and provide technical input for problem resolution.
- Develop and maintain software, deployment automation, test automation, and supporting tools using appropriate engineering practices.
- Monitor application uptime, performance, data quality, and AI solution effectiveness; identify and remediate reliability issues.
- Maintain technical documentation to reflect accurate and current production installations, deployment procedures, integrations, and AI model or prompt behavior.
- Review pull requests and collaborate with developers on user stories, test cases, code quality, and production readiness.
- Actively engage in development-team activities associated with brainstorming new solutions and refining current solutions.
- Drive technical efforts that lead to successful software project delivery and measurable improvements in deployment efficiency.
- Possess technical depth and applied experience in multi-layer solutioning, performance tuning, solution debugging, incident triage and remediation, and usability improvement.
- Travel to physical plant locations for workshops, discovery, testing, and deployment activities.
- Work during manufacturing plant downtime, which may include weekends, second shift, third shift, and holidays.
Your Skills & Abilities (Required Qualifications)
- Bachelor’s degree in Computer Science, Engineering, Information Technology, or a related field.
- 5+ years of experience integrating applications with industrial PLCs, robots , or other automation equipment in a manufacturing environment .
- Hands-on experience deploying and maintaining control-room or manufacturing applications on shop-floor IT infrastructure .
- Experience with industrial protocols, PLCs, manufacturing equipment , and plant-floor data collection and integration.
- Experience designing, integrating, or operationalizing AI/ML solutions in an enterprise or manufacturing environment.
- Experience with generative AI, large language models , prompt engineering, retrieval-augmented generation, agentic workflows, or AI-assisted software and script development.
- Experience developing or applying predictive maintenance, anomaly detection, forecasting, or other manufacturing analytics models.
- Experience creating natural-language query or conversational interfaces for operational, manufacturing, or time-series data.
- Experience implementing safeguards for AI solutions , including validation, access control, data protection, explainability, monitoring, and human-in-the-loop review.
- Databases: Oracle, SQL Server, PostgreSQL , or comparable relational and time-series data technologies.
- Web Application Servers: Tomcat, IIS , or comparable platforms.
- Infrastructure: Server provisioning, virtual machines, networking, clustered servers, and plant data-center environments.
- Operating systems and platforms: Linux, UNIX, Windows Server , and cloud technologies.
- Tools: Cursor, Confluence, ServiceNow, GitHub, Fortify, SonarLint/SonarQube, Artifactory, and JIRA.
- Strong .NET/C# development skills.
- Strong Python or PowerShell scripting skills, with the ability to build deployment, integration, and test automation.
- Experience with Agile teams that regularly deliver software while practicing code review and automated testing.
- Proven experience diagnosing issues from browser to application, infrastructure, network, database, and industrial systems.
- Experience with IT enterprise security concepts and implementation.
- Kepware experience, including configuring an IoT Gateway to allow a PLC to communicate with an upper-level application through Kepware, importing tags, and supporting automatic tag generation.
People Skills
- Excellent verbal and written communication skills, with the ability to communicate and translate feedback, needs, risks, and solutions across IT, engineering, plant operations, and business stakeholders.
- Creative problem-solving skills that deliver elegant solutions to complex technical and operational issues.
- Strong teamwork focus and the ability to foster collaboration within and across teams.
- A high degree of
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