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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in leading AI security product strategies, integrating advanced AI features, and ensuring secure deployment architectures. Proficient in collaborating with enterprise partners and translating technical requirements into actionable product roadmaps.
Highest-signal resume keywords
Technical Product ManagementAI/ML Security EngineeringModel Context Protocol (MCP) SpecificationAgentic Frameworks (LangChain, AutoGen, CrewAI, LlamaIndex)Active Defense Mechanics (Llama Guard, NeMo Guardrails)
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
CybersecurityCloud SecuritySystems ArchitectureTechnical Specifications WritingArchitectural Diagrams Creation
Soft Skills
Communication with CISOsCollaboration with Engineers
Tools & Technologies
AI GatewayModel Context Protocol GatewayAutomated Red-Teaming ToolsData Loss Prevention Tools
Industry Keywords
Zero-Trust Data BoundariesWorkload Identity GovernanceNon-Human Identity (NHI) GovernanceMachine-to-Machine OAuthPrompt Injection Defense
Tech Stack
Tools & technologiesCloudCyber Security
About the role
Key responsibilities & impact- Lead the 0-to-1 product strategy, ecosystem integrations, and secure deployment architecture of the next-generation AI security portfolio
- Own technical interfaces, joint roadmaps, and secure integrations with top LLM/foundation model providers
- Co-develop secure-by-design API standards, secure context passing, and zero-trust data boundaries
- Align emerging security frameworks and integrate or optimize runtime guardrails, prompt shields, and firewall systems for frontier models
- Define technical requirements and prototype advanced AI features integrating with AI Gateway and Model Context Protocol Gateway
- Secure the data plane between agents, client applications, and external LLM tools
- Support productization of AI guardrails, automated LLM red-teaming/evaluation pipelines, and data loss prevention
- Serve as primary technical point of contact for enterprise design partners during complex rollouts
- Collaborate daily with Forward Deployed Engineers to architect, install, and troubleshoot production-grade AI applications
- Translate field telemetry, deployment architectures, and customer friction points into the core product platform and model development roadmap
Requirements
What you’ll need- 8+ years of technical product management, systems architecture, or engineering experience in cybersecurity, cloud security, or platform engineering
- At least 3+ years dedicated to AI/ML security or engineering
- Practical understanding of the Model Context Protocol (MCP) specification, remote MCP server governance, and secure routing protocols
- Hands-on experience with agentic frameworks such as LangChain, AutoGen, CrewAI, or LlamaIndex
- Strong grasp of Workload Identity, Non-Human Identity (NHI) governance, and machine-to-machine OAuth
- Thorough understanding of active defense mechanics such as Llama Guard and NeMo Guardrails, prompt injection defense, data extraction prevention, and automated red-teaming/evaluation tools
- Ability to write precise technical specs, architectural diagrams, and code snippets
- Ability to communicate security posture to enterprise CISOs and Chief AI Officers in customer briefings
- BS or MS in Computer Science, Computer Engineering, or equivalent highly technical field
Benefits
Comp & perks- Incentive compensation
- Bonus
- Restricted stock units
- Benefits package
- Reasonable accommodations for candidates