Senior AI Product Manager (Agent Platform)

This position is listed on behalf of a partner company, which manages all applications and next steps. Our partner is looking for a Senior AI Product Manager (Agent Platform) based in the United States.

The Senior AI Product Manager will lead the development, adoption, and evolution of an enterprise AI agent platform designed to help teams build, deploy, govern, and scale intelligent AI solutions. This role combines strategic product leadership with hands-on execution, shaping platform capabilities and creating an intuitive experience for developers and business teams. You will drive product adoption, guide early-stage implementations, and establish reusable frameworks that make deploying secure, reliable AI agents faster and easier. Working closely with engineering, infrastructure, security, risk, and compliance teams, you will integrate enterprise governance directly into the platform experience. You will also define product roadmaps, oversee release cycles, and measure success through real-world usage and business outcomes. This is an exciting opportunity for an experienced product leader to shape enterprise AI innovation in a collaborative, fast-evolving technology environment.

Accountabilities

Drive product adoption and go-to-market strategy: Own the platform adoption lifecycle, develop onboarding strategies, recruit pilot teams, and turn successful implementations into reusable reference solutions. Track adoption and measure the impact of product initiatives.
Optimize the builder experience: Manage the end-to-end user journey, from platform discovery and onboarding to development and deployment. Improve self-service capabilities, documentation, quick-start guides, and reference patterns to reduce friction and accelerate implementation.
Define and prioritize the product roadmap: Manage incoming platform requirements and maintain a transparent roadmap covering essential capabilities such as agent registration, model routing, identity management, logging, and governed access.
Embed governance, security, and compliance: Collaborate with security, infrastructure, risk, and compliance teams to incorporate enterprise controls into standard development workflows. Identify and resolve barriers to adoption while ensuring that compliant implementation paths remain efficient and accessible.
Manage the product release lifecycle: Lead alpha, beta, and general availability (GA) releases for platform components, establish clear entry and exit criteria, and coordinate delivery across interconnected products and technical teams.
Measure product performance and business value: Define and monitor success metrics that go beyond agent registration, including production use cases enabled, time to value, recurring usage, adoption rates, and measurable business outcomes.
Align cross-functional stakeholders: Build strong working relationships with engineering, security, infrastructure, risk, compliance, and business teams to align priorities, resolve technical challenges, and support platform growth.
Promote scalable AI capabilities: Establish repeatable product patterns and governed workflows that enable teams across the organization to develop and deploy AI agents securely and consistently.
Requirements
Education: Bachelor's degree in marketing, business, or a related field, or equivalent practical experience.
Product management experience: Significant experience in product management, with demonstrated ownership of a platform, developer tools, APIs, infrastructure, or shared services used by multiple teams.
Generative AI expertise: Strong understanding of applied generative AI, agentic systems, large language models (LLMs), retrieval and grounding techniques, tool use, and orchestration.
Platform adoption and developer experience: Proven ability to drive platform adoption, improve builder or developer journeys, and create practical documentation, onboarding materials, quick-start guides, and reusable implementation patterns.
Governance and security knowledge: Solid understanding of enterprise security controls, including authentication, identity management, least-privilege access, audit logging, and risk tiering.
Technical proficiency: Ability to configure systems, work with APIs, use AI-assisted tools, and interpret execution logs and traces. Familiarity with technical formats and tools such as Markdown, JSON, and YAML is important.
Communication and stakeholder influence: Excellent written and verbal communication skills, with the ability to translate complex technical concepts into clear product priorities and influence technical, security, and executive stakeholders without relying on direct authority.
Strategic and analytical thinking: Ability to prioritize competing demands, define measurable outcomes, make informed product decisions, and balance user experience with enterprise security and governance requirements.
Preferred experience: Background working with AI agent platforms, model gateways, integration gateways, or tool-access protocols such as the Model Context Protocol (MCP).
Additional advantages: Experience transitioning an internally focused platform to external customers or partners; familiarity with AI governance, model risk, agent registries, or responsible AI programs; and experience launching low-code or no-code tools alongside developer-focused capabilities.
Industry knowledge: Experience in regulated industries such as payments, financial technology, or healthcare is an advantage, as is familiarity with cloud identity and access management (IAM), service-to-service authentication, and AI evaluation frameworks.
Professional attributes: Strong ownership, adaptability, problem-solving skills, and the ability to thrive in a fast-moving environment where technology, user needs, and business priorities evolve rapidly.
Benefits
Annual base salary: $125,300–$154,100, depending on qualifications, skills, competencies, and relevant experience.
Performance-based compensation: Eligibility for a quarterly or annual bonus, subject to role-specific requirements and applicable compensation plans.
Health coverage: Medical, dental, and vision insurance.
Retirement savings: Access to a retirement savings plan.
Paid time off: Paid leave to support personal needs, rest, and work-life balance.
Health and flexible spending accounts: Access to health savings accounts (HSA) and flexible spending accounts (FSA), subject to eligibility.
Insurance protection: Life insurance and disability insurance.
Learning and development: Tuition reimbursement and opportunities to support ongoing professional growth.
Employee well-being: A comprehensive benefits package designed to support physical, financial, and professional well-being.
Remote work: A full-time remote position based in the United States.
Innovative work environment: The opportunity to shape enterprise AI capabilities, influence product strategy, and collaborate with multidisciplinary teams on emerging technologies.
Inclusive workplace: A commitment to diversity, inclusion, equal opportunity, and reasonable accommodations for qualified individuals with disabilities.