Principal Product Manager - Knowledge Bases & Ask AI

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.

\n

Accountabilities

• 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.

Requirements

• 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 filtering, query rewriting, re-ranking, source attribution, structured-data retrieval, knowledge lifecycle management, LLM orchestration, tool/function calling, agent routing, context management, memory, evaluation, observability, APIs, and webhooks.

• Strong understanding of the difference between generated language and grounded answers, retrieval quality and final-answer quality, conversational interfaces and agentic systems, demonstrations and dependable production products, and model intelligence and overall system reliability.

• Proven ability to design evaluation strategies for retrieval, answers, plans, tools, actions, artefacts, permissions, and memory, supported by meaningful datasets and production telemetry.

• Strong systems-thinking skills, with the ability to connect identity, permissions, agency and location context, CRM data, Knowledge Bases, memory, tools, workflows, billing, and reporting into a coherent platform.

• Experience designing AI products capable of modifying business data or executing consequential actions, with strong judgment around permissions, approvals, auditability, reversibility, sensitive information, and customer trust.

• Experience simplifying technically sophisticated products for non-technical users and designing intuitive experiences for complex workflows.

• Experience with multi-tenant SaaS and environments involving agencies, resellers, franchises, enterprises, or multi-location businesses.

• Strong customer orientation, including willingness to personally inspect AI conversations, retrieval outputs, tool traces, failures, support issues, and user configurations.

• Excellent analytical and problem-solving capabilities, with the ability to distinguish model failures, retrieval failures, tool failures, UX issues, and expectation mismatches.

• Strong commercial judgment across activation, retention, packaging, usage-based pricing, infrastructure and AI costs, gross margins, and ecosystem economics.

• Ability to influence senior stakeholders and multiple cross-functional teams without relying on direct reporting authority.

• Excellent written and verbal communication skills, including the ability to create strategy documents, product requirements, platform contracts, architectural decisions, evaluation plans, executive updates, and launch narratives.

• High ownership, intellectual honesty, adaptability, and execution velocity in a remote-first, high-context environment.

• Ability to make difficult prioritisation decisions across answer quality, action coverage, customer experience, platform extensibility, privacy, reliability, technical debt, revenue, and cost.

• Experience with AI copilots, enterprise assistants, enterprise search, knowledge-management products, structured-data question answering, agent ecosystems, browser automation, or developer platforms is highly desirable.

• Familiarity with metrics such as retrieval recall, top-k precision, grounded-answer rate, tool-selection accuracy, action success rate, task completion, repeat usage, latency, cost per successful outcome, ingestion success, and support-ticket rates is a strong advantage.

Benefits

• Fully remote opportunity for candidates based in India.

• Opportunity to own a foundational AI product platform with broad impact across a large B2B SaaS ecosystem.

• High level of autonomy and ownership as a senior individual contributor.

• Exposure to advanced AI technologies including LLM orchestration, RAG, agent systems, memory, retrieval, automation, and multimodal AI experiences.

• Opportunity to influence multiple product and engineering teams and shape shared AI platform standards.

• Remote-first environment designed around initiative, clarity, collaboration, and execution.

• Opportunity to work on products serving businesses across multiple industries and geographies.

• Strong learning and career-growth potential within a well-funded and profitable technology environment.

• Culture focused on rapid experimentation, continuous improvement, customer value, and lean product development.

• Opportunity to mentor product managers and contribute to the broader development of AI product strategy and practices.

\nHow Jobgether works:

We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

Why Apply Through Jobgether?

Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.

#LI-CL1