Advanced Software Engineer - AI Reliability Engineering
New
G
General Dynamics Mission SystemsDefense software
Source API remote eligibility restrictions: United StatesFull-TimeMiddle
Salary118,519 - 131,482 USD per year
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Job Details
- Experience
- Bachelor's degree plus a minimum of 5 years of relevant experience; or Master's degree plus 3 years of relevant experience.
- Required Skills
- PythonAgileFull Stack DevelopmentJavascriptTypeScriptCI/CDDevOps
Requirements
- Bachelor's degree in Computer Science, Software Engineering, or a related field.
- Bachelor's degree plus a minimum of 5 years of relevant experience, or a Master's degree plus 3 years of relevant experience.
- Proficiency in Python and/or JavaScript/TypeScript.
- Full-stack development experience.
- Experience with web application frameworks, relational databases, and REST API design.
- 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.
- Experience building AI/ML capabilities or LLM-based applications is preferred.
- Experience with cloud platforms such as Azure or AWS and containerization tools such as Docker or Kubernetes is preferred.
- Familiarity with manufacturing systems such as MES or ERP, or industrial data integration such as OPC-UA or MQTT, is preferred.
- Experience in defense or aerospace industries is preferred.
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.
- Gather requirements firsthand by embedding with operations users at company sites.
- Own solutions end to end, from requirements and design through development, deployment, and support.
- Design data models that capture, normalize, and flow operations data into a central data warehouse.
- Build integrations between enterprise systems, including ERP, PLM, and MES.
- Embed AI/ML capabilities such as predictive quality, anomaly detection, natural-language data access, and autonomous decision support into applications.
- Partner with operations teams and IT infrastructure teams on cloud deployment, security compliance, and DevSecOps practices.
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