Security Harness Engineer

Join a pioneering team focused on building advanced, production-grade AI capabilities that drive secure software development across the entire SDLC. As a Sr. Security Harness Engineer, you will design and deploy innovative AI solutions, shaping secure agentic workflows, AI-generated code assurance, and enterprise-scale integrations. This is a fully onsite role in Round Rock, TX, offering the chance to impact critical enterprise systems and collaborate with some of the brightest minds in software security and AI., Architect, build, and deploy AI-enabled tools that automate and strengthen software security throughout the development lifecycle

• Develop specification-driven workflows translating requirements into secure, verifiable software implementations
• Implement guardrails and policy enforcement for AI-generated code, ensuring high standards of quality, reliability, and safety
• Create developer-assist and verification tooling for automated security checks, supply-chain analysis, and release audits
• Integrate solutions with enterprise systems (source control, CI/CD, ticketing, security scanning, identity platforms) using REST, GraphQL, and Model Context Protocol (MCP)
• Apply robust architecture practices-service boundaries, data models, secure defaults, observability, and extensibility
• Partner with engineering, security, product, and leadership teams to define requirements, evaluate trade-offs, and promote adoption
• Drive solutions from requirements analysis through design, implementation, deployment, and enterprise adoption

Proven track record developing and deploying AI-based solutions in production environments with measurable impact

• Advanced programming proficiency in Python, TypeScript/JavaScript, Go, or similar languages, with strong focus on code quality, testing, and maintainability
• Hands-on experience with modern AI and LLM development: context engineering, agentic system design, context-window management, token budgeting, and AI evaluation
• Experience designing model context, agentic retrieval, memory architectures, enterprise data grounding, and structured outputs
• Engineering experience with agent loops, multi-agent orchestration, and tool/function calling
• Expertise optimizing AI workloads for production cost and latency
• Deep understanding of software architecture: API design, event-driven systems, scalable/extensible data modeling
• Experience integrating multiple systems/platforms including REST/GraphQL APIs, CI/CD pipelines, cloud services, and enterprise tooling
• Effective communicator and collaborator, able to convey technical concepts to both engineering and business audiences
• Demonstrated ability to work independently across the full delivery lifecycle

Preferred Skills

• Experience applying AI in security domains (application security, DevSecOps, code analysis, threat modeling, firmware security, or supply chain security)
• Familiarity with secure-by-design practices and frameworks (OWASP, OWASP Top 10 for LLM Applications, NIST SSDF)
• Experience with MCP, building agent skills/tools, or extending AI coding assistants (Claude Code, GitHub Copilot, Cursor, or Devin)
• Experience with AI evaluation frameworks, guardrails, prompt/response caching, and LLMOps in production
• Bachelor’s or Master’s degree in Computer Science or related field, or equivalent practical experience, Required Skills & Qualifications Demonstrated experience developing and deploying AI-based solutions in production environments with measurable business or operational impact Strong programming proficiency in Python Typescript/Javascript Go or a similar language with disciplined use of testing code quality and maintainability practices Hands-on experience with modern AI and LLM development including context engineering agentic system design context-window management token budgeting and evaluation of AI quality Reliability and safety Experience designing model context through agentic retrieval and search memory architectures enterprise data grounding and structured outputs Experience engineering agent loops multi-agent and sub-agent orchestration and tool/function calling Ability to optimize AI workloads for production cost and latency Solid understanding of software architecture and systems design including API design event-driven patterns and data modeling for scalability and extensibility Experience developing or deploying applications with large-scale impact such as a broad user base high transaction volume or organization-wide adoption Experience integrating multiple systems and platforms including REST or GraphQL APIs CI/CD pipelines Cloud Services and enterprise tooling Demonstrated ability to work independently across the full delivery lifecycle: requirements analysis solution design Implementation Deployment stakeholder engagement and accountability for results Strong communication and collaboration skills with the ability to convey technical concepts to engineering and business audiences

Long-term contract with a leading Fortune 500 company

• Opportunity to own and deliver AI solutions at enterprise scale
• Collaborate with top-tier security, engineering, and AI experts
• Influence technical direction and shape organizational security posture
• Fully onsite - work in a collaborative, innovation-driven environment