Job Title :

AI Security Engineer Location:

Round Rock, TX - Onsite

Duration:

Long Term contract Position Summary We are seeking a highly skilled AI Engineer (Security) to design, develop, and deploy enterprise-grade AI and autonomous agent solutions within a large-scale security organization. The ideal candidate will have hands-on experience taking AI/LLM solutions from concept through production, with a strong focus on agentic AI, enterprise architecture, secure-by-design engineering, and AI-powered security solutions. This role will help drive the organization's transition from traditional automation to autonomous, agentic AI capabilities. The successful candidate will work closely with engineering, security, product, architecture, and business stakeholders to identify high-value opportunities, design scalable solutions, and deliver measurable business outcomes. Candidates should have experience working in large enterprise environments and demonstrate the ability to build and scale production AI solutions across complex organizations. Key Responsibilities

• Design, develop, test, and deploy AI-powered and autonomous agent solutions for enterprise business and security workflows.
• Build agentic workflows, agent loops, multi-agent systems, sub-agents, and tool/function-calling capabilities.
• Translate business and stakeholder requirements into secure, scalable, and production-ready AI solutions.
• Take ownership of the complete solution lifecycle, including requirements gathering, architecture, development, testing, deployment, monitoring, and adoption.
• Develop AI capabilities that support the SDLC, including:
• Specification-driven development
• AI-generated code assurance
• Security guardrails and policy enforcement
• Automated design and security reviews
• Dependency and software supply-chain analysis
• Static and dynamic analysis orchestration
• Release and compliance audit support
• Integrate AI solutions with enterprise platforms such as source control, CI/CD pipelines, ticketing systems, security scanning tools, identity platforms, cloud services, and internal applications.
• Develop integrations using REST/GraphQL APIs, webhooks, MCP (Model Context Protocol), and other enterprise protocols.
• Apply strong software architecture and systems-design principles, including service boundaries, data modeling, observability, scalability, extensibility, and secure defaults.
• Engineer effective context management, including retrieval, search, memory architectures, enterprise data grounding, and structured outputs.
• Optimize LLM token consumption, context windows, cost, latency, and overall production performance.
• Develop and implement AI evaluation practices to measure accuracy, reliability, safety, quality, and business impact.
• Evaluate emerging AI technologies, agentic frameworks, retrieval and memory systems, evaluation frameworks, guardrails, and LLMOps capabilities.
• Partner with security, engineering, product, architecture, and leadership teams to evaluate technical trade-offs and drive adoption.
• Establish reusable AI engineering patterns, standards, documentation, and best practices.
• Promote secure-by-design and secure-by-default principles throughout AI solution development.
• Mentor team members and contribute to technical enablement through documentation, demonstrations, and knowledge sharing. Required Qualifications
• Proven experience developing and deploying AI/LLM solutions into production environments.
• Hands-on experience building autonomous AI agents or agentic workflows for enterprise business p