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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in leading product strategy and secure deployment architecture for AI security solutions, with a strong focus on integrating advanced security frameworks and protocols. Proficient in technical product management and collaboration with enterprise partners to drive innovative AI features and secure integrations.
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
Technical Specifications WritingArchitectural Diagrams CreationCode Snippet DevelopmentSecure Routing ProtocolsData Loss Prevention ControlsAutomated Red-Teaming ToolsZero-Trust Data BoundariesPrompt Injection DefenseMachine-to-Machine OAuthWorkload Identity Governance
Soft Skills
Communication with CISOsCollaboration with EngineersProblem-Solving
Tools & Technologies
AI GatewayModel Context Protocol GatewayProduction-Grade AI ApplicationsTelemetry Analysis
Industry Keywords
CybersecurityCloud SecurityPlatform EngineeringAI Security PortfolioSecure-by-Design API Standards
Tech Stack
Tools & technologiesCloudCyber Security
About the role
Key responsibilities & impact- Lead 0-to-1 product strategy, ecosystem integrations, and secure deployment architecture for F5’s next-generation AI security portfolio
- Own technical interfaces, joint roadmaps, and secure integrations with top LLM/foundation model providers
- Lead technical product partnerships to co-develop secure-by-design API standards, secure context passing, and zero-trust data boundaries
- Drive alignment on emerging security frameworks and integrate runtime guardrails, prompt shields, and firewall systems with frontier models
- Define technical requirements and prototype AI features integrating with AI Gateway and Model Context Protocol Gateway
- Secure the data plane between agents, client applications, and external LLM tools
- Productize AI guardrails, automated LLM red-teaming/evaluation pipelines, and data loss prevention controls
- Serve as primary technical 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