Advanced Software Engineer - AI Reliability Engineering

General Dynamics Mission Systems, Inc•,

6d•$118,519 - $131,482•Remote

About The Position

The Advanced Software Engineer will join General Dynamics Mission Systems’ Operations Technology team, a forward-deployed engineering group that embeds with users to understand workflows, define requirements, and build custom AI-native solutions. The role spans the full development lifecycle, from gathering requirements directly from manufacturing-floor operators and engineers to designing architectures, shipping production code, and supporting deployed systems. Work includes software development, data architecture, and emerging manufacturing technologies such as Agentic AI, IoT, machine learning, robotics, computer vision, and digital twins. The team builds purpose-built systems to replace legacy applications and establish a connected data foundation across the enterprise. The engineer will develop full-stack applications for manufacturing execution, data integration, and operational intelligence; build APIs, data pipelines, and enterprise integrations; and embed AI/ML capabilities in applications. The role involves working directly with operations users at GDMS sites, taking ownership from requirements through deployment and support, and collaborating across multiple operations functions and with IT infrastructure teams. This is a remote position. U.S. citizenship is required due to the nature of work performed within GDMS facilities.

Requirements

Bachelor's degree in Software Engineering or a related Science, Technology, Engineering, or Mathematics field and at least 5 years of relevant experience, or a Master's degree and at least 3 years of relevant experience.
Bachelor's degree in Computer Science, Software Engineering, or a related field.
U.S. citizenship is required.
Proficiency in Python and/or JavaScript/TypeScript, with full-stack development experience.
Experience with web application frameworks, relational databases, and REST API design.
Strong understanding of modern development practices, including DevOps, Agile, and CI/CD.
Ability to work independently and take ownership of deliverables in a fast-paced environment.
Strong problem-solving and communication skills.

Nice To Haves

Experience building AI/ML capabilities or LLM-based applications.
Proficiency with AI coding assistants such as Claude Code, Copilot, or Cursor in professional workflows.
Experience with cloud platforms such as Azure or AWS and containerization technologies such as Docker or Kubernetes.
Familiarity with manufacturing systems such as MES and ERP, or industrial data integration such as OPC-UA and MQTT.
Experience in the defense or aerospace industries.

Responsibilities

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 for enterprise-scale deployment across operations sites.
Use modern development tools, including AI coding assistants, to deliver software rapidly.
Embed with operations users at GDMS sites to understand workflows and define requirements firsthand.
Own problems end to end, including requirements, design, development, deployment, and support.
Translate complex business processes into working software through rapid prototyping and iterative delivery.
Design data models to capture, normalize, and flow operations data into a central data warehouse.
Build integrations between enterprise systems such as ERP, PLM, and MES, as well as other business applications.
Build systems that capture critical manufacturing data digitally at the point of work and eliminate shadow data.
Embed AI/ML capabilities into applications, including predictive quality, anomaly detection, natural-language data access, and autonomous decision support.
Use large language models and AI coding agents as core tools in the development workflow.
Explore and evaluate emerging manufacturing technologies, including IoT, robotics, digital twins, and computer vision, for the team's technology roadmap.
Identify opportunities to apply AI for continuous improvement and innovation.
Partner with Manufacturing, Supply Chain, Quality, Facilities, EH&S, Government Property, and other Operations personnel across multiple sites.
Work with IT infrastructure teams on cloud deployment, security compliance, and DevSecOps practices.
Communicate technical concepts clearly to non-technical stakeholders.