AI Knowledge Product Architect

eGain delivers trusted AI to transform customer experience for some of the largest brands in the world. TheeGain AI Knowledge Hub helps modernize knowledge management to improve customer experience, transform customer service, and reduce operational costs.Trusted for decades by leading enterprises in financial services, insurance, telecommunications, retail, healthcare, and government, eGain combines content, AI, and analytics to power knowledge agents and assistants for customers, employees, and AI bots. Our AI Knowledge Hub, AI Agent, Composer, and Evaluator products are deployed in mission-critical environments where accuracy, governance, and scale are non-negotiable.The OpportunityWe’re looking for an experienced AI Knowledge Product Architect to drive the strategy, roadmap, and execution of our AI-powered knowledge management products. In this role, you’ll sit at the intersection of generative AI, knowledge management, and customer experience — shaping products that transform how enterprises deliver trusted knowledge to customers, contact center agents, and AI bots.At eGain, we think of enterprise AI as a five-layer stack:InfrastructureDataAI ModelsKnowledgeApplicationsKnowledge is instruction for your AI. Knowledge along with data is infrastructure on which you build reliable agentic systems – it’s the layer that turns generic AI into trusted enterprise AI — and that’s where this role lives. We’re specifically looking for candidates who want to bring that foundational depth to the Knowledge layer.This is a high-impact, high-visibility role for a product leader who is passionate about AI, obsessed with customers, and motivated by building category-defining products.What You Will DoOwn the vision, strategy, and architecture of the AI Knowledge Hub as enabler for Customer Service Automation & Enterprise AI.Advance the product & architectural foundation for enterprise knowledge management — the platform, infrastructure, and frameworks powering knowledge.Drive product roadmap to transform Content into Trusted Knowledge – a single source of truth for all value-added app building and human consumption.What You Will Bring6–10 years of product management experience in layers 1–3 of the AI stack — Infrastructure, Data, or AI Models. Examples: enterprise data and AI platforms like Databricks or Snowflake; model serving and inference platforms; ML infrastructure.Proven track record shipping AI infrastructure products at enterprise scale.Deep technical command of modern AI — LLMs, embeddings, vector databases, RAG, agentic patterns, and evaluation frameworks.Experience with enterprise customers in regulated industries — financial services, insurance, telecommunications, healthcare, or government.Bachelor’s degree in Computer Science, Engineering, or a related technical field.Master’s degree preferredPreferred experience with knowledge management platforms and fluency in knowledge modeling, ontologies, taxonomies, retrieval architectures, and enterprise content lifecycle.Track record of taking platform products through the full lifecycle — from 0 1 invention through scaling to enterprise adoption preferred.Why eGainThe chance to shape the future of AI-powered knowledge management at a category leader trusted by the world’s largest brands.A collaborative, fast-paced environment with seasoned product, engineering, and AI leaders.Direct exposure to enterprise customers and senior leadership.Competitive compensation, equity, and comprehensive benefits.A mission-driven team committed to delivering trusted AI Knowledge at scaleOur Hiring Process is “Easy with eGain”Step 1Written testAptitude section – this is a GRE style test (60 minutes or less)Functional section – this is a take-home testStep 2Panel interview (in-person at eGain Sunnyvale office)Next stepEmail your resumé to [email protected] with the position title “AI Knowledge Product Architect” in the email subject.CompensationThe salary is $200,000 per year.Stock options.Please note that the compensation package can vary based on the candidate’s qualifications and experience level.