Principal Product Manager

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Principal Product Manager - Knowledge Bases & Ask AI based in India.

This is a senior individual-contributor product leadership role focused on shaping the future of AI-powered assistance for a complex B2B SaaS platform. You will own the long-term strategy for Knowledge Bases and Ask AI, creating the intelligence layer that helps users understand information and complete meaningful work through natural language. The role spans AI assistants, retrieval systems, agent orchestration, workflow execution, CRM data, permissions, and multi-tenant SaaS. You will influence multiple Product, Engineering, Design, Data, Security, and GTM teams while establishing scalable platform standards. Success will require balancing AI quality, customer experience, reliability, privacy, extensibility, and commercial outcomes. This is an ideal opportunity for a highly technical and strategic product leader who enjoys solving ambiguous problems and building foundational platforms at scale.

• Define and drive the long-term product vision, strategy, roadmap, and platform architecture for Knowledge Bases and Ask AI, establishing the principles that guide how users retrieve information, generate plans, invoke tools, execute actions, and interact with AI.
• Own the end-to-end Ask AI experience across chat, voice, conversation history, memory, templates, artefacts, scheduled tasks, tools, actions, agent routing, browser interaction, feedback, permissions, approvals, auditability, usage, and lifecycle management.
• Lead the Knowledge Base platform strategy across source ingestion, extraction, parsing, chunking, embeddings, indexing, metadata, retrieval, re-ranking, citations, freshness, versioning, permissions, testing, and observability.
• Establish a shared context model connecting identity, agency and location, permissions, business profiles, CRM data, product configuration, memory, Knowledge Bases, Brand Voice, and previous tool outputs.
• Develop robust evaluation frameworks and test datasets to measure retrieval quality, answer accuracy, tool selection, action success, memory usage, permissions, latency, cost, and overall business outcomes.
• Partner with AI, engineering, infrastructure, and platform teams on LLM orchestration, model routing, RAG, embeddings, hybrid search, agent planning, memory, tool invocation, caching, scalability, reliability, and cost management.
• Enable product teams to expose capabilities safely through Ask AI by establishing shared standards for actions, permissions, approvals, errors, results, specialised agents, templates, skills, and artefacts.
• Improve Knowledge Base quality-management workflows through retrieval testing, source inspection, stale-content detection, crawl diagnostics, document-processing monitoring, conflict detection, and customer-facing recommendations.
• Define scalable models for reusable, inherited, bundled, and marketplace-distributed Knowledge Bases across agencies and locations.
• Partner with Design to simplify Knowledge Base creation, source management, testing, maintenance, agent attachment, onboarding, approvals, artefact interaction, and error recovery.
• Establish instrumentation and metrics across discovery, first prompt, useful responses, successful actions, repeat usage, Knowledge Base creation, ingestion, retrieval testing, agent attachment, retention, and production adoption.
• Work closely with Security, Legal, Privacy, and Trust teams to establish standards for data isolation, access control, memory, sensitive information, browser automation, source permissions, retention, auditability, and abuse prevention.
• Define safeguards for destructive actions, bulk changes, financial operations, external communications, and compliance-sensitive workflows, including appropriate approval and audit mechanisms.
• Partner with Product Marketing, Support, Implementation, Account Management, Finance, and Revenue teams on positioning, customer education, adoption, packaging, pricing, cost controls, commercial limits, and support reduction.
• Maintain a strong competitive and technology perspective across AI copilots, enterprise search, knowledge management, CRM assistants, agent platforms, browser agents, and workflow automation.
• Evaluate external model providers, retrieval technologies, document-processing systems, vector databases, re-ranking solutions, browser technologies, and strategic partnerships.
• Influence product strategy across Conversation AI, Voice AI, Agent Studio, CRM, automation, communications, commerce, and other AI-powered capabilities.
• Act as a senior product thought partner to Product, Engineering, Design, Data, Security, GTM, Finance, and executive leadership while mentoring other PMs and raising the quality of AI product strategy across the organisation.

• 12+ years of product management experience, with a strong track record across complex B2B SaaS, AI assistants, enterprise search, knowledge management, workflow automation, CRM, developer platforms, or AI-agent products; demonstrated scope and outcomes are more important than an exact number of years.
• Previous experience operating as a Principal PM, Staff PM, Lead PM, product founder, or equivalent senior individual contributor responsible for a business-critical platform.
• Demonstrated ability to define strategy across multiple teams and deliver sustained customer and commercial outcomes rather than focusing only on individual feature delivery.
• Proven experience building production AI products that combine answers, context, tools, workflows, and actions.
• Strong technical fluency in several areas including retrieval-augmented generation, document ingestion and parsing, chunking, embeddings, vector search, keyword and hybrid retrieval, metadata