Senior Manufacturing Systems Engineer

General Dynamics Mission Systems, Inc • ,

2d • $142,696 - $158,303 • Remote

About The Position

Imagine a world-class engineering environment. Now add a team of exceptional talent along with technologies that are so advanced they are often classified. That is what you will find at General Dynamics Mission Systems. Here you will join a team of exceptional engineers as they invent the technologies, products and services that help our service members, intelligence analysts and first responders keep our nation safe. If you want the chance to build things that matter, it is time to bring your talent to General Dynamics Mission Systems.
You will be part of the Operations Technology team, a forward deployed engineering group that embeds directly with users to understand workflows, define requirements, and build custom AI-native solutions from scratch. As the Manufacturing Systems Engineer, you are the technical anchor for how we architect manufacturing systems. Your first mission is to lead the design and build of a custom MES that scales across all operations sites. You will work across the full development lifecycle: gathering requirements firsthand from operators and engineers on the manufacturing floor, designing a scalable, modular architecture, writing and shipping production code, and supporting the systems you build. The scope spans software, data architecture, and emerging manufacturing technologies including Agentic AI, IoT, machine learning, robotics, computer vision, and digital twins.
This is a greenfield build, not a configuration job. We build purpose-built, best-of-breed systems around our best process and connect them from day one, instead of buying a COTS platform and bending our process to fit it. You will architect the system, not configure a COTS platform.

Requirements

• Bachelor's degree in Software Engineering, or related Science, Technology, Engineering or Mathematics field, plus a minimum of 8 years of relevant experience; or Master's degree, plus 6 years relevant experience.
• Manufacturing Systems Architecture
• Apply manufacturing systems standards and patterns (ISA-95, equipment/work hierarchy, genealogy, traceability) to a modern, modular, cloud-native build
• Make the build-versus-buy and technology-stack decisions that set the foundation for every system that follows
• Bring outside-in perspective: translate how leading manufacturers run their operations into what good looks like here
• Define the scope, schedule, and expectations for the work you lead, operating with limited direction on ambiguous, undefined problems
• Serve as a technical lead, providing work direction and mentorship to other engineers as the team grows
• Software Development & Deployment
• Design, develop, test, and deploy full-stack web applications for manufacturing execution, data integration, and operational intelligence
• Build AI-native applications with intelligence embedded from the architecture up
• Develop APIs, data pipelines, and integration layers that connect business systems into a unified data architecture
• Write clean, scalable code with a focus on enterprise-scale deployment across all operations sites
• Deploy in weeks, not months, using modern development tools including AI coding assistants
• Forward Deployed Engineering
• Embed directly with operations users at GDMS sites to understand workflows and define requirements firsthand
• Own problems end to end: architecture, requirements, design, development, deployment, and support
• Translate complex manufacturing processes into working software through rapid prototyping and iterative delivery
• Build for the user, not the specification. The operator's experience matters more than the feature list.
• Data Architecture & Integration
• Design data models that capture, normalize, and flow manufacturing data into a central data warehouse
• Build integrations between enterprise systems (ERP, PLM, CMMS, MRO) and shop-floor equipment using industrial protocols (OPC-UA, MQTT) where applicable
• Eliminate shadow data by building systems that capture critical manufacturing data digitally at the point of work
• AI & Emerging Technology
• Embed AI/ML capabilities into applications: predictive quality, anomaly detection, natural language data access, autonomous decision support
• Leverage large language models and AI coding agents as core tools in the development workflow
• Evaluate emerging manufacturing technologies (IoT, robotics, digital twins, computer vision) for integration into the team's roadmap
• Cross-Functional Collaboration
• Partner with Manufacturing, Supply Chain, Quality, Facilities, EH&S, Government Property, and all Operations personnel across multiple sites
• Work closely with IT infrastructure teams on cloud deployment, security compliance, and DevSecOps practices
• Communicate technical concepts clearly to non-technical stakeholders

Nice To Haves

• Agentic AI
• IoT
• machine learning
• robotics
• computer vision
• digital twins
• ISA-95
• equipment/work hierarchy
• genealogy
• traceability
• cloud-native build
• OPC-UA
• MQTT
• predictive quality
• anomaly detection
• natural language data access
• autonomous decision support
• large language models
• AI coding agents
• DevSecOps practices

Responsibilities

• Lead the architecture of a custom MES and the broader manufacturing systems landscape, designed to scale from one site to all operations sites
• Apply manufacturing systems standards and patterns (ISA-95, equipment/work hierarchy, genealogy, traceability) to a modern, modular, cloud-native build
• Make the build-versus-buy and technology-stack decisions that set the foundation for every system that follows
• Bring outside-in perspective: translate how leading manufacturers run their operations into what good looks like here
• Define the scope, schedule, and expectations for the work you lead, operating with limited direction on ambiguous, undefined problems
• Serve as a technical lead, providing work direction and mentorship to other engineers as the team grows
• Design, develop, test, and deploy full-stack web applications for manufacturing execution, data integration, and operational intelligence
• Build AI-native applications with intelligence embedded from the architecture up
• Develop APIs, data pipelines, and integration layers that connect business systems into a unified data architecture
• Write clean, scalable code with a focus on enterprise-scale deployment across all operations sites
• Deploy in weeks, not months, using modern development tools including AI coding assistants
• Embed directly with operations users at GDMS sites to understand workflows and define requirements firsthand
• Own problems end to end: architecture, requirements, design, development, deployment, and support
• Translate complex manufacturing processes into working software through rapid prototyping and iterative delivery
• Build for the user, not the specification. The operator's experience matters more than the feature list.
• Design data models that capture, normalize, and flow manufacturing data into a central data warehouse
• Build integrations between enterprise systems (ERP, PLM, CMMS, MRO) and shop-floor equipment using industrial protocols (OPC-UA, MQTT) where applicable
• Eliminate shadow data by building systems that capture critical manufacturing data digitally at the point of work
• Embed AI/ML capabilities into applications: predictive quality, anomaly detection, natural language data access, autonomous decision support
• Leverage large language models and AI coding agents as core tools in the development workflow
• Evaluate emerging manufacturing technologies (IoT, robotics, digital twins, computer vision) for integration into the team's roadmap
• Partner with Manufacturing, Supply Chain, Quality, Facilities, EH&S, Government Property, and all Operations personnel across multiple sites
• Work closely with IT infrastructure teams on cloud deployment, security compliance, and DevSecOps practices
• Communicate technical concepts clearly to non-technical stakeholders

Benefits

• An exciting career path with opportunities for continuous learning and development.
• Research oriented work, alongside award winning teams developing practical solutions for our nation’s security
• Flexible schedules with every other Friday off work, if desired (9/80 schedule)
• Competitive benefits, including 401k matching, flex time off, paid parental leave, healthcare benefits, health & wellness programs, employee resource and social groups, and more

What This Job Offers

• Job Type: Full-time
• Career Level: Senior