Senior Full-Stack AI Engineer (Agentic Systems)

The Senior Full-Stack AI Engineer - Agentic Systems will build and scale NISTCompliance.ai, Quzara’s AI-enabled cybersecurity compliance platform. This senior, hands-on role designs, codes, tests, and ships production software across the full stack. It also covers building AI capabilities with leading large language models, including agentic workflows, retrieval-augmented generation (RAG), and document intelligence. The ideal candidate is an AI-native engineer who uses AI-assisted development tools to deliver secure, reliable, production-ready software, not prototypes., * Design, build, test, and ship production features across frontend, backend, APIs, databases, and AI services.

• Build AI-powered product capabilities using leading large language models and generative AI platforms.
• Design and implement agentic workflows involving tool use, structured outputs, multi-step tasks, and human oversight.
• Develop and improve retrieval-augmented generation (RAG), semantic search, document intelligence, and knowledge-retrieval capabilities.
• Integrate AI capabilities into existing application workflows and enterprise systems.
• Build reliable evaluation, testing, monitoring, and observability for AI-powered functionality.
• Develop secure, scalable APIs and backend services supporting AI-enabled applications.
• Use AI-assisted coding tools extensively for repository analysis, development, testing, debugging, refactoring, and code review.
• Diagnose complex engineering problems across application, AI, data, and cloud layers.
• Contribute to architecture, engineering standards, code reviews, and technical mentoring.
• Evaluate emerging AI technologies and rapidly determine which capabilities are suitable for production use.

Marginal Functions of the Job

• Other duties as assigned

Normal Work Schedule

This is a full-time position. Standard business hours are Monday through Friday 8:30 AM to 5:30 PM. Additional time outside of these hours may be needed to complete the essential functions of the job.

What We’re Looking For: We’re looking for an AI-native, hands-on engineer who builds and ships production-ready software across the full stack, not just AI prototypes. You use tools like Claude Code, Codex, GitHub Copilot, and Cursor to work faster, and you back them with sound engineering judgment, rigorous testing, and strong security practices. This is an engineering role, not a data science or research position., * 7+ years of professional software engineering experience.

• Demonstrated experience owning complex software features or systems from design through production.
• Strong full-stack development experience.
• Advanced proficiency in Python.
• Strong proficiency with JavaScript/TypeScript and modern web application development.
• Experience building and integrating REST APIs and production backend services.
• Experience with relational databases such as PostgreSQL or equivalent.
• Hands-on experience integrating commercial LLMs such as Anthropic Claude, OpenAI models, or comparable platforms into production applications.
• Practical experience with agentic AI, tool/function calling, structured model outputs, and multi-step AI workflows.
• Experience building RAG or similar retrieval-based AI applications.
• Significant hands-on experience with AI-assisted development environments such as Claude Code, Codex, GitHub Copilot, Cursor, Windsurf, or similar tools.
• Strong understanding of software engineering fundamentals including testing, source control, CI/CD, observability, security, and maintainable application architecture.
• Experience with Docker and modern cloud application development.
• Ability to independently take ambiguous product requirements and turn them into production software.
• U.S. citizenship required., * Experience designing AI agents or multi-agent systems.
• Familiarity with Model Context Protocol (MCP) or comparable agent/tool integration approaches.
• Experience with AI orchestration frameworks and agent SDKs.
• Experience with LLM evaluation, observability, benchmarking, or LLMOps platforms.
• Experience with vector search, embeddings, document processing, or enterprise knowledge systems.
• Experience building multi-tenant enterprise SaaS applications.
• Experience with Microsoft Azure or other major cloud platforms.
• Cybersecurity, compliance, GRC, or federal technology experience is helpful but not required.
• Experience mentoring other software engineers.