Principal Product Manager – Agentic AI Platform

About This Position:

As a Principal Product Manager for Agentic AI Platform at G-P, you will play a pivotal role in shaping our Agentic AI strategy and driving the success of platform capabilities that enable AI-powered experiences across our products and operations. You will work at the intersection of AI, platform services, developer experience, security, data, and enterprise SaaS.

You will be expected to define how agents, tools, APIs, workflows, evaluation frameworks, permissions, and governance models come together to create reliable, secure, and scalable AI capabilities. This is a platform product role with a strong AI focus. The ideal candidate has deep platform product management experience, strong curiosity about AI, and the ability to translate emerging technology into practical product outcomes.

What you will do: 

• Lead the end-to-end lifecycle of Agentic AI platform capabilities, from strategy and discovery to roadmap, execution, launch, adoption, and continuous improvement.
• Define and drive key AI platform capabilities, including agents, tools, action interfaces, API integrations, orchestration patterns, evaluation frameworks, observability, guardrails, and human-in-the-loop workflows.
• Partner with engineering, data, security, and product teams to build scalable AI-powered capabilities using cloud-native, SaaS, microservices, serverless, and event-driven architectures.
• Own the product strategy for how agents answer questions, assist users, take actions, access data, use tools, and safely interact with business systems.
• Work with business product teams to identify and prioritize high-value agentic use cases across customer experience, professional experience, reporting, onboarding, compliance, support, and internal operations.
• Drive a platform approach for AI by creating reusable patterns, shared capabilities, clear standards, and developer-friendly interfaces that can be adopted across multiple teams and products.
• Define AI quality and evaluation requirements, including golden datasets, test cases, pass/fail criteria, trace reviews, regression testing, and production monitoring.
• Collaborate with identity, security, and platform teams to ensure agentic actions follow proper authentication, authorization, permissions, auditability, privacy, and compliance controls.
• Drive a developer-centric approach for Agentic AI platform services by improving discoverability, documentation, onboarding, usability, and adoption for internal product and engineering teams.
• Use AI-powered tools in your own product workflow to improve discovery, analysis, documentation, prioritization, decision-making, and execution.
• Work with cross-functional stakeholders to align priorities, gather requirements, manage trade-offs, and ensure successful adoption of AI platform capabilities.
• Drive KPIs that reflect real-world AI and platform impact, including adoption, task completion, answer quality, automation success, deflection, operational efficiency, satisfaction, and reliability.

What we are looking for: 

Minimum Requirements:

• Experience: 15+ years of product management experience, including owning and driving large-scale technology platforms, AI products, developer-facing products, or enterprise SaaS capabilities across multiple lifecycle stages.
• Agentic AI Product Thinking: Strong understanding of how AI, LLMs, agents, tools, workflows, automation, and orchestration can be applied to enterprise SaaS products. Ability to think beyond chatbot experiences and define how AI can help users complete meaningful tasks and business outcomes.
• AI Quality and Governance: Familiarity with AI evaluation methods such as golden datasets, test suites, trace analysis, human review, LLM-as-a-judge, regression testing, and production monitoring. Strong awareness of AI risks around accuracy, privacy, security, explainability, permissions, and compliance.
• Technical Depth: Deep familiarity with cloud platforms, SaaS business models, microservices, serverless computing, event-driven architectures, API-first design, data integrations, and modern enterprise architecture. Ability to translate technical possibilities into product outcomes.
• Platform Product Management: Strong platform mindset with experience creating reusable capabilities, standards, interfaces, and services that support multiple product teams and business use cases.
• Developer Experience: Ability to build platform services with empathy for developers, including onboarding, authentication, documentation, observability, service discoverability, and lifecycle needs. Prior experience with Internal Developer Portals such as Backstage is a plus.
• Identity, Security, and Access Control: Experience with authentication, authorization, role-based access, policy-based access, API security, OpenAPI, or platform security workflows is highly desirable.
• Internal Stakeholder Collaboration: Demonstrated ability to work closely with internal customers, especially PMs and engineering leaders of business applications. Skilled in building strong relationships, understanding needs, and creating alignment.
• Prioritization and Decision-Making: Excellent skills in managing and prioritizing requirements in situations with conflicting needs, ambiguity, emerging technology, and platform dependencies.
• Execution Rigor: High ownership mindset. Ability to balance long-term vision with short-term wins. Comfortable driving specs, writing docs, aligning teams, and getting into details.
• Effective Communication: Outstanding communication skills, with the ability to explain complex AI and platform concepts clearly to technical, business, and executive audiences.
• Documentation and Requirements: Expertise in creating clear PRDs, strategy documents, product briefs, specifications, and operating models.
• Strategic and Analytical Thinking: Strong problem-solving ability and strategic thinking. Proficient in analyzing market trends, user feedback, platform usage, and AI performance data to inform product strategy.
• Data-Driven Approach: Proficiency in defining and tracking KPIs and metrics to measure AI quality, platform adoption, user satisfaction, automation success, and business impact.
• Agile Methodologies: Experience with Agile and Scrum methodologies, fostering a culture of continuous improvement and adaptability.
• Educational Background: Solid technical foundation, preferably with a degree in Computer Science, Engineering, Data Science, or a related field. Advanced degrees such as M.S. or MBA are a plus.