AI-Assisted Full-Stack Engineer

Turning Point Global Solutions•Washington, DC

1d•Hybrid

About The Position

Turning Point Global Solutions (TurningPoint) is seeking a Full-Stack Software Engineer to build and support applications on a small, forward-deployed team serving a federal customer. The engineer will use AI-assisted development tools to help design, implement, test, debug, and document software while ensuring delivered applications meet accessibility, security, and quality requirements. The role is based in the Washington, DC Metro Area and follows a hybrid schedule with three days per week on-site in DC. Applicants must be eligible for Public Trust and be a U.S. citizen or green card holder/EAD holder, and must be able to obtain a favorable background investigation. Turning Point Global Solutions is an information technology services company serving federal, state, and local government organizations and commercial clients. Founded in 2002, the privately funded and debt-free company provides mission-critical solutions and reports CMMI Maturity Level 5 for development and Level 3 for services.

Requirements

Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent.
At least 5 years of hands-on full-stack development experience, including building and supporting production applications.
At least 1 year of experience delivering Generative AI capabilities, such as LLM integration, RAG pipelines, embeddings, vector databases, or AI workflow orchestration.
Strong proficiency in Python and JavaScript/TypeScript, with experience in React or Angular, RESTful APIs, and relational and NoSQL databases.
Experience using AI-assisted development tools to write, debug, refactor, test, and document software, and ability to critically review and validate AI-generated code.
Experience with at least one major cloud platform (AWS, Azure, or Google Cloud) and containerized deployments using Docker, CI/CD pipelines, and automated security scans.
Experience with automated testing, AI output evaluation, secure coding, and accessibility requirements, including Section 508 and WCAG 2.1 AA.
Familiarity with LLM security risks, human-in-the-loop controls, and applicable federal security and Responsible AI requirements.
Experience with Git, code reviews, and Agile development practices.
Ability to obtain a favorable background investigation and meet the federal customer’s citizenship or work authorization requirements.
Eligible for Public Trust; must be a U.S. citizen or green card holder/EAD holder.

Nice To Haves

At least 7 years of software development experience, including work on federal agency programs.
Experience with agentic AI/MCP tooling, AI security testing, ATO documentation, or AWS Bedrock/SageMaker.
Generative AI or ML certification, such as Azure AI, AWS, Google Cloud, NVIDIA, or CAIP.
Active or prior favorably adjudicated government background investigation.

Responsibilities

Build and support full-stack applications, including accessible user interfaces, back-end APIs, database integration, and workflow automation.
Use approved AI-assisted development tools to help design, write, refactor, debug, test, and document code.
Review and validate AI-generated code for corrections, security, maintainability, and compliance with project requirements and applicable federal standards.
Develop interfaces that meet Section 508 and WCAG 2.1 AA accessibility requirements.
Build LLM integrations, RAG pipelines, vector search, and agentic workflows using MCP, with human-in-the-loop oversight.
Apply secure development practices aligned with customer requirements, the OWASP Top 10 for LLM Applications, and NIST AI RMF.
Run functional, performance, and adversarial testing, including prompt injection and jailbreak testing, and evaluate AI output for accuracy, hallucination, bias, and safety.
Build and maintain CI/CD and MLOps pipelines with security scans and TEVV gates.
Monitor production applications and AI capabilities; troubleshoot issues; support incident response, maintenance, and helpdesk requests.
Work in Agile sprints with code and prompt reviews, and contribute to Responsible AI documentation.