Sr. Systems Engineer - Manufacturing Plant Floor Systems
General Motors
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Benefits offered by this job
Job summary
General Motors is seeking a Sr. Systems Engineer to lead deployment, modernization, and ongoing support of software used across GM manufacturing plants.
You will build AI-centric, repeatable deployment environments, deconstruct existing processes, and drive automation and reliability across the plant footprint. The ideal candidate has deep CIMPLICITY/SCADA, OPC UA/DA, and PLC-to-MES experience, plus hands-on AI/ML integration, deployment automation, and security governance.
Qualifications
- Bachelor’s degree in CS/Engineering/IT or related field.
- 5+ years integrating applications with industrial PLCs, robots, or automation equipment.
- Hands-on in deploying and maintaining shop-floor applications on IT infrastructure.
- Experience with industrial protocols, PLCs, and data integration.
- Experience designing or operationalizing AI/ML in manufacturing.
- Experience with generative AI, LLMs, and AI-assisted development.
- Experience with predictive maintenance and time-series analytics.
- Experience building natural-language interfaces for plant data.
- Experience implementing safeguards for AI, including validation and access control.
- Knowledge of databases (Oracle, SQL Server, PostgreSQL) and web apps (Tomcat/IIS).
Responsibilities
- Deconstruct deployment processes to make them AI-centric, secure, and scalable.
- Deploy, configure, update, and maintain shop-floor software on IT infra.
- Install and configure virtual servers in plant data centres.
- Coordinate testing and deployment with project teams.
- Identify repeatable actions for automation via scripting and CI/CD.
- Design and implement AI/ML capabilities for PLC/SCADA scripts and analytics.
- Validate AI-generated scripts and configurations for safety and traceability.
- Collaborate with in-plant resources to verify functionality and data quality.
- Maintain documentation for production installations and AI behavior.
- Review PRs and collaborate on code quality and production readiness.
- Travel to plant locations for workshops, testing, and deployments.
- Work during plant downtime and weekends as needed.
Skills
Education
Tools
Job description
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.
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.
- 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 centres 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 behaviour.
- 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 behaviour.
- 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.
- 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.
- 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 business insight, creativity, decision‑making skill, drive for results, negotiation ability, peer‑relationship development, and technical learning agility.
- A customer‑centric mindset and enthusiasm for complex systems, reliable software, responsible AI, and measurable business outcomes.
- Deep experience with GE Digital CIMPLICITY (SCADA), OPC UA/DA, and PLC‑to‑MES data integration.
- Previous manufacturing, plant‑floor, industrial automation, or operational technology experience.
- Demonstrated experience deploying AI/ML solutions into production and monitoring their performance and value.
- Experience with AI‑assisted DevOps, MLOps, model lifecycle management, or LLMOps.
- Experience with time‑series data, industrial historians, predictive maintenance, anomaly detection, or digital twins.
- Experience with enterprise LLM platforms, vector databases, or retrieval‑augmented generation architectures.
GM does not provide immigration‑related sponsorship for this role. Do not apply for this role if you will need GM immigration sponsorship now or in the future. This includes direct company sponsorship, entry of GM as the immigration employer of record on a government form, and any work authorization requiring a written submission or other immigration support from the company (e.g., H1‑B, OPT, STEM OPT, CPT, TN, J‑1, etc). This role is categorized as hybrid. This means the selected candidate is expected to report to a specific location at least 3 times a week {or other frequency dictated by their manager}. Relocation benefits are available for candidates who qualify under company policy.
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We encourage interested candidates to review the key responsibilities and qualifications for each role and apply for any positions that match their skills and capabilities. Applicants in the recruitment process may be required, where applicable, to successfully complete a role‑related assessment(s) and/or a pre‑employment screening prior to beginning employment. To learn more, visit How we Hire.
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