Agentic AI Security Engineer, Lead The Opportunity:
As organizations adopt AI systems that can reason, use tools, and take action, they need engineers who understand both how these systems work and how to secure them. We’re looking for an AI / ML engineer who can combine hands-on development, security expertise, and architectural thinking to help our customers deploy agentic AI securely and responsibly.
As a security-focused AI / ML Engineer on our team, you’ll design, build, and evaluate secure AI applications and agentic workflows. You’ll examine how models, agent orchestration, tools, data sources, and enterprise infrastructure interact, identify security risks, and develop practical controls throughout the system lifecycle. You’ll turn emerging research and complex technical requirements into working prototypes, reusable architecture patterns, and clear technical guidance.
You’ll collaborate with AI engineers, cybersecurity spe cia lists, architects, and mission stakeholders to develop solutions that balance capability, security, and operational needs. Your work will help technology leaders and implementation teams understand how to move from AI experimentation to secure, governed deployment.
What You’ll Work On:
Design and validate secure architectures for generative AI applications, AI agents, and multi-agent systems, including model access, orchestration, tool execution, memory, and retrieval augmented generation.
Develop prototypes and reference implementations to demonstrate security controls and evaluate architectural tradeoffs.
Assess AI systems for risks such as prompt injection, sensitive data exposure, excessive permissions, u nsa fe tool execution, and compromised integrations.
Design and implement controls for agent identity, least privilege access, execution isolation, tool authorization, data protection, and human approval of consequential actions.
Develop architecture diagrams, data flow diagrams, t rus t boundary models, and technical documentation that explain system behavior, control placement, and implementation requirements.
Establish evaluation and monitoring approaches for agent behavior, security, reliability, and policy compliance, including t race ability across model interactions and tool calls.
Translate security and governance requirements into engineering practices, including testing, version control, change management, audit trails, and rollback procedures.
Evaluate emerging models, agent frameworks, integration protocols, and security tools, and communicate findings and recommendations to technical and non-technical audiences.
Provide day-to-day technical leadership to engineers.
Conduct design reviews, guide architectural decisions, and raise the overall technical bar of the team.
Join us. The world can’t wait.
You Have:
8+ years of experience in sof tware engineering or AI / ML engineering, including developing and deploying AI / ML systems
Experience developing in Python and applying sof tware engineering practices, including Git, automated testing, code review, and dependency management
Experience building applications using large language models, including tool use, retrieval augmented generation, and agent orchestration
Experience designing or evaluating system architectures involving APIs, data pipelines, model services, and enterprise integrations
Experience applying cybersecurity principles to sof tware or AI systems, including identity and access management, t rus t boun dari es, secure data handling, and threat modeling
Experience with traditional ML approaches and algorithms and their applications to cybersecurity
Knowledge of NIST security and risk management frameworks, including SP 800-53 and AI Risk Management Framework, and Zero T rus t Architecture principles, including identity-based access, least privilege, and continuous verification
Knowledge of AI-specific security risks and approaches for evaluating and mitigating vulnerabilities in generative AI and agentic…