Senior Full-Stack AI Engineer – Agentic Systems

Quzara LLC

. Build and scale NISTCompliance.ai, Quzara's AI-enabled cybersecurity compliance platform .

Posted 9/24/2026full-timeRemote • United StatesSenior💰 $125,000 - $175,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates advanced proficiency in Python and JavaScript/TypeScript for full-stack development, with a strong focus on building and integrating AI-powered applications and REST APIs. Capable of designing complex software features and systems while ensuring security, observability, and maintainability.

Highest-signal resume keywords

Full-Stack DevelopmentPython ProgrammingAI-Powered Application DevelopmentREST API IntegrationAI-Assisted Development Tools

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Applicant Tracking System Keywords

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Hard Skills

PythonJavaScriptTypeScriptREST APIsPostgreSQLAI DevelopmentRAG ApplicationsDockerCI/CDSoftware Engineering Fundamentals

Soft Skills

Problem SolvingTechnical MentoringIndependent Work

Tools & Technologies

Claude CodeCodexGitHub CopilotCursorWindsurfMicrosoft Azure

Industry Keywords

CybersecurityComplianceGRCAI OrchestrationMulti-Agent Systems

Tech Stack

Tools & technologies

AzureCloudCyber SecurityDockerJavaScriptPostgresPythonTypeScript

About the role

Key responsibilities & impact

Build and scale NISTCompliance.ai, Quzara's AI-enabled cybersecurity compliance platform
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 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 determine which capabilities are suitable for production use
Perform other duties as assigned

Requirements

What you’ll need

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
Preferred: Experience designing AI agents or multi-agent systems
Preferred: Familiarity with Model Context Protocol (MCP) or comparable agent/tool integration approaches
Preferred: Experience with AI orchestration frameworks and agent SDKs
Preferred: Experience with LLM evaluation, observability, benchmarking, or LLMOps platforms
Preferred: Experience with vector search, embeddings, document processing, or enterprise knowledge systems
Preferred: Experience building multi-tenant enterprise SaaS applications
Preferred: Experience with Microsoft Azure or other major cloud platforms
Cybersecurity, compliance, GRC, or federal technology experience is helpful but not required
Preferred: Experience mentoring other software engineers