Quick Overview
Seniority
Mid Senior
Work mode
Hybrid
Location
Dayton, OH, United States
Posted
Yesterday
MicroservicesAWSScrumC#Google CloudJavaKanbanPythonGenerative AIAzureJavaScriptTypeScriptAgileData AnalysisPrompt EngineeringCI/CDRAGSystem Design
Job Description
Position Summary
A premier federal technology solutions firm is seeking a veteran Senior Software Engineer to architect, deploy, and modernize high-performance enterprise systems. This position centers on modern application engineering, cloud-native frameworks, AI-driven automation, and deep systems integration. The selected engineer will develop high-impact analytical tools that optimize large-scale logistics, asset sustainment, and supply chain operations.
In this role, you will build robust software applications, secure APIs, and intelligent automation pipelines that transform complex data sets into actionable, mission-critical assets. This role provides an excellent opportunity to work at the intersection of DevSecOps, cloud engineering, and advanced data analytics in support of a vital, high-visibility defense platform.
Core Responsibilities
Systems Engineering & Architecture
- Application Development: Design, build, validate, and launch highly scalable, secure enterprise platforms, APIs, and microservices.
- Cloud Architecture: Establish secure, cloud-native system blueprints and steer architecture decisions across the full technology stack.
- Infrastructure Modernization: Drive continuous integration and deployment (CI/CD) using containerized environments, migrating legacy architectures to modern cloud infrastructures.
- Technical Excellence: Uphold rigorous engineering principles, including distributed source control, automated testing suites, code reviews, and technical documentation.
- Security & Compliance: Ensure all software products adhere strictly to secure coding standards and federal cybersecurity mandates.
- Operational Support: Oversee production environment monitoring, system troubleshooting, and long-term application maintenance.
Artificial Intelligence & Automation
- AI Implementation: Architect and embed advanced AI functionalities—including Large Language Models (LLMs), Generative AI, Retrieval-Augmented Generation (RAG), and autonomous workflows—into live production systems via authorized frameworks.
- Engineering Velocity: Leverage AI-assisted development utilities to accelerate delivery timelines and optimize code reliability.
- Innovation: Review and test emerging automation frameworks to guide practical adoption across the organization.
Stakeholder Collaboration
- Requirement Translation: Convert multi-layered operational needs into production-grade software by collaborating closely with data analysts and program stakeholders.
- Strategic Insight: Construct forecasting algorithms, predictive models, and decision-support systems that convert data into strategic intelligence.
- Technical Guidance: Offer mentorship to engineering team members and help define standardized development practices.
Position Requirements
- Clearance: Must be a U.S. Citizen with the active capability to obtain a Secret Security Clearance .
- Education: Bachelor’s degree in a technical or engineering discipline.
- Core Experience: Extensive professional background in software development, application design, systems integration, or automated engineering.
- Programming Languages: Strong proficiency in a modern backend language—such as Python, Java, C#, or JavaScript/TypeScript —backed by recent, hands-on production deployment experience.
- System Design: Proven track record building, scaling, and maintaining distributed microservices or service-oriented architectures (SOA).
- Methodology: Active experience working within Agile frameworks, specifically Scrum or Kanban environments.
- Cloud Platforms: Practical experience hosting and maintaining applications in major cloud ecosystems (AWS, Azure, or Google Cloud Platform ), utilizing containerization tools.
- Integration: Background in stitching together disparate enterprise systems to create cohesive software solutions.
- Professional Skills: Superior problem-solving capabilities alongside clear technical writing and interpersonal communication skills.
Preferred Qualifications
- Background deploying Generative AI models, prompt engineering structures, or smart automation tools within enterprise products.
- Familiarity with orchestration platforms and agentic framework designs.
- Experience building data-heavy applications that emphasize predictive forecasting, statistical modeling, or operational optimization.
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