Artificial Intelligence (AI) - Assisted Software Engineer (Mid)

Koniag Government Services, LLC•Huntsville, AL

17h•$100,000 - $120,000•Onsite

About The Position

Koniag Government Services is seeking a mid-level Artificial Intelligence (AI)-Assisted Software Engineer to support KMS and a government customer in Huntsville, Alabama. This is an onsite role requiring an active SECRET clearance. The engineer will modernize legacy production applications into secure, scalable, maintainable cloud-based web applications, combining software engineering fundamentals with practical use of AI coding assistants and agentic development tools. The role involves analyzing complex codebases, preserving business functionality and data integrity, identifying technical debt and security risks, and implementing controlled, test-driven modernization. The engineer will develop cloud-ready full-stack applications, use AI tools under appropriate human oversight, and establish automated testing, CI/CD, documentation, and repeatable deployment practices. Work includes collaboration with engineering, cybersecurity, infrastructure, and mission stakeholders to meet operational, performance, and security requirements. The position requires a BS in Computer Science or Engineering, 24 to 84 months of relevant hands-on experience, CompTIA Security+ before joining, and an active SECRET clearance.

Requirements

Bachelor of Science in Computer Science or Engineering.
24 to 84 months of minimum hands-on or relevant experience.
Active SECRET clearance required for consideration.
CompTIA Security+ certification required before joining.
Practical experience with modern AI coding assistants and agentic development tools.
Experience with cloud-based development and application modernization.
Ability to analyze complex legacy codebases, preserve existing functionality, identify technical debt, and implement controlled refactoring.
Experience or capability in full-stack web development, including browser-based interfaces, backend services, RESTful APIs, and relational databases.
Experience or capability with automated testing, Git-based workflows, CI/CD, and cloud deployment practices.
Ability to evaluate AI-generated code and apply appropriate human oversight before production use.

Responsibilities

Analyze enterprise and legacy applications, including their architecture, dependencies, data flows, business rules, data models, and integration points.
Design and implement modern, cloud-ready, full-stack web application architectures.
Refactor and migrate legacy functionality into modular, maintainable components and services while preserving business behavior and data integrity.
Use approved AI-assisted coding and agentic development tools for code comprehension, refactoring, debugging, testing, and documentation.
Guide AI-generated changes with repository context, task specifications, architectural constraints, and appropriate human review and validation.
Evaluate AI-generated code for correctness, security, maintainability, performance, and compliance with project standards.
Integrate AI-assisted development into Git branching, code review, testing, and CI/CD workflows, while following policies for AI platforms and sensitive information.
Develop and deploy applications in cloud-hosted environments such as Google Cloud Platform, Microsoft Azure, or AWS.
Build and maintain containerized development and deployment environments using Docker or comparable technologies.
Implement automated build, test, security scanning, and deployment pipelines.
Apply infrastructure configuration, secrets management, environment separation, and secure deployment practices.
Support development, test, and production environments through repeatable deployment and release processes.
Incorporate monitoring, structured logging, troubleshooting, performance optimization, and operational observability into application design.
Design, develop, and maintain responsive browser-based interfaces, secure backend services, business logic, and RESTful APIs.
Work with relational databases, optimize SQL queries, and support schema modernization and controlled database migrations.
Implement authentication, authorization, input validation, logging, exception handling, and other foundational application security controls.
Integrate new application components with existing enterprise systems and legacy data sources.
Develop characterization, unit, integration, and regression tests before and after refactoring.
Support incremental modernization strategies that minimize operational risk, downtime, and disruption to end users.
Diagnose and resolve production defects and performance issues during modernization.
Collaborate with developers, technical leads, project managers, cybersecurity and infrastructure personnel, and mission stakeholders.
Participate in Agile planning, backlog refinement, technical design reviews, demonstrations, and sprint execution.
Use Git-based version control and peer review workflows to manage software changes.
Maintain technical documentation, architectural diagrams, API specifications, and deployment instructions.
Communicate engineering tradeoffs and identify opportunities to improve application quality, engineering efficiency, and delivery.
Share effective AI-assisted engineering practices with teammates.