Principal Product Manager – Agentic AI Platform
New
G
G-PSaaS Platform
India (Remote-First)Full-TimePrincipal
Salary not disclosed
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Job Details
- Experience
- 15+ years
- Required Skills
- Product ManagementMicroservices
Requirements
- 15+ years of product management experience, including owning and driving large-scale technology platforms, AI products, developer-facing products, or enterprise SaaS capabilities.
- Strong understanding of how AI, LLMs, agents, tools, workflows, automation, and orchestration can be applied to enterprise SaaS products.
- Familiarity with AI evaluation methods such as golden datasets, test suites, trace analysis, human review, LLM-as-a-judge, regression testing, and production monitoring.
- Deep familiarity with cloud platforms, SaaS business models, microservices, serverless computing, event-driven architectures, API-first design, and data integrations.
- Strong platform mindset with experience creating reusable capabilities, standards, interfaces, and services.
- Experience with Internal Developer Portals such as Backstage is a plus.
- Experience with authentication, authorization, role-based access, policy-based access, API security, OpenAPI, or platform security workflows.
- Ability to work closely with internal customers, especially PMs and engineering leaders of business applications.
- Expertise in creating clear PRDs, strategy documents, product briefs, specifications, and operating models.
- Degree in Computer Science, Engineering, Data Science, or a related field; Advanced degrees such as M.S. or MBA are a plus.
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.
- 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.
- Drive a developer-centric approach for Agentic AI platform services by improving discoverability, documentation, onboarding, usability, and adoption for internal product and engineering teams.
- Drive KPIs that reflect real-world AI and platform impact, including adoption, task completion, answer quality, automation success, deflection, operational efficiency, satisfaction, and reliability.
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