Principal Product Manager – Agentic AI Platform
New
Our diverse, remote-first teams are essential to our success.Full-TimePrincipal
Salary not disclosed
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Job Details
- Experience
- 15+ years of product management experience
- Required Skills
- AgileCloud ComputingProduct ManagementMicroservicesSaaS
Requirements
- 15+ years of product management experience, including owning large-scale technology platforms, AI products, developer-facing products, or enterprise SaaS.
- Strong understanding of Agentic AI, LLMs, agents, tools, workflows, and orchestration.
- Familiarity with AI evaluation methods such as golden datasets, test suites, trace analysis, and human review.
- Deep familiarity with cloud platforms, SaaS business models, microservices, serverless computing, and event-driven architectures.
- Experience creating reusable platform capabilities, standards, and interfaces.
- Ability to build developer-centric services, including onboarding, documentation, and observability.
- Experience with authentication, authorization, role-based access, and API security.
- Proficiency in Agile and Scrum methodologies.
- Solid technical foundation, preferably with a degree in Computer Science, Engineering, or Data Science.
Responsibilities
- 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.
- 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.
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