Job DescriptionAI Security Product Manager
We are seeking an
AI Security Product Manager to lead the strategy, roadmap, and execution of security capabilities that enable safe, scalable adoption of AI across the enterprise. This role sits at the intersection of
product management, cybersecurity, engineering, and architecture, translating emerging AI security risks into practical platform capabilities, controls, and operating processes. This role is in Pittsburgh PA or Lake Mary, FL
The ideal candidate brings a strong product mindset, along with
prior experience in engineering and architecture, and can define product direction for capabilities such as
AI governance tooling, model and agent security controls, prompt and data protection, AI observability, policy enforcement, identity and access controls, and secure AI lifecycle workflows. This person must be able to work across technical and non-technical stakeholders, prioritize high-impact outcomes, and drive delivery in a complex enterprise environment.
Key Responsibilities- Define and own the product vision, strategy, and roadmap for AI security capabilities across the enterprise.
- Translate AI security risks, regulatory expectations, and control requirements into product requirements and prioritized backlog items.
- Partner with cybersecurity, engineering, architecture, data, legal, risk, and governance teams to deliver secure-by-design AI capabilities.
- Drive product development for controls supporting AI platforms, agents, model integrations, and related workflows.
- Use prior engineering and architecture experience to shape practical, scalable, and technically credible product requirements.
- Shape requirements for areas such as:
- AI application and agent security
- Model access governance
- Prompt and data protection
- AI activity logging and observability
- Policy enforcement and runtime guardrails
- Identity, authorization, and least privilege controls
- Third-party AI risk management
- Develop business cases, success metrics, and adoption plans for new AI security capabilities.
- Prioritize features and investments based on risk reduction, enterprise value, technical feasibility, and adoption needs.
- Create clear product requirements, user stories, acceptance criteria, and rollout plans.
- Lead cross-functional execution from concept through pilot, launch, and scale.
- Establish feedback loops with users, security teams, and platform teams to continuously improve product effectiveness.
- Track external market developments, regulatory changes, and emerging threats relevant to AI security.
- Communicate roadmap progress, decisions, dependencies, and risks to senior stakeholders in a concise, decision-ready manner.
Qualifications- 10+ years of experience across product management, engineering, architecture, cybersecurity, enterprise technology, or related fields.
- Former hands-on experience in engineering and architecture roles, with the ability to engage credibly with technical teams and influence solution direction.
- Experience working in or alongside cybersecurity, cloud, identity, developer platform, or governance functions.
- Strong understanding of AI/ML and GenAI concepts, with the ability to translate technical and risk concepts into product strategy.
- Experience defining product roadmaps and delivering complex enterprise products across multiple stakeholder groups.
- Strong ability to write product requirements and convert ambiguity into clear execution plans.
- Familiarity with AI security concepts such as:
- prompt injection and misuse risks
- model and agent access controls
- human-in-the-loop and approval patterns
- logging, monitoring, and traceability
- Third-party model and vendor risk
- Excellent communication and stakeholder management skills.
- Ability to operate effectively in a fast-moving, highly cross-functional environment.
Preferred Qualifications- Experience in AI security, cloud security, identity and access management, application security, or security architecture.
- Experience with enterprise AI platforms, AI governance processes, or model risk/control frameworks.
- Familiarity with secure SDLC, platform security patterns, and policy/control implementation.
- Experience working with regulated environments and audit or compliance stakeholders.
- Demonstrated ability to launch 0-to-1 or early-stage enterprise security capabilities.
Success ProfileThe successful candidate will:
- Bring clarity to a fast-evolving AI security landscape.
- Balance speed, usability, and control effectiveness.
- Influence across organizational boundaries without relying solely on formal authority.
- Convert risk themes into practical products and measurable outcomes.
- Apply engineering and architecture experience to ensure product direction is implementable, scalable, and aligned to enterprise realities.
- Drive execution with discipline while keeping long-term platform strategy in view.
Example Outcome Areas- Launch governance-enabling product features that improve secure onboarding of AI use cases.
- Improve visibility into AI usage, data flows, and security-relevant activity.
- Reduce risk from overprivileged agents, unmanaged integrations, or weak authorization models.
- Introduce scalable control patterns for AI applications and services.
- Support enterprise adoption of AI by making security requirements more usable, measurable, and operationally efficient.
