Senior Product Manager

Vectara

13h•Hybrid

About The Position

Vectara provides a Trusted Generative AI platform that allows organizations to rapidly create a ChatGPT-like experience (an AI assistant) which is grounded in the data, documents and knowledge that they have. Our serverless RAG-as-a-Service also solves critical problems required for enterprise adoption, namely: reduces hallucination, provides explainability / provenance, enforces access control, allows for real-time updatability of the knowledge and mitigates intellectual property / bias concerns from large language models (LLMs). Our founding team includes industry pioneers and experts in neural information retrieval and distributed systems from Google. Join us as we pursue our mission to help the world find meaning through trusted Generative AI for Enterprise Applications. People at Vectara are passionate about ensuring customers take advantage of breakthroughs in applied Artificial Intelligence (AI) to solve real-world technology & business problems today. Our team is a group of unquestionable all-stars in their respective fields of computer science and business from Google, Cloudera, Splunk, MongoDB, Elastic and more. Role Overview: Vectara is looking for a Product Manager to bridge the gap between our technical capabilities and our commercial success. This is a high-impact, cross-functional role for someone who can navigate the space between Product, Sales, and Engineering. You will be responsible for translating market signals into a concrete roadmap and ensuring our go-to-market strategy—specifically around pricing and positioning—is as sophisticated as the AI we build. We need a leader who is comfortable representing the product directly to customers and refining our competitive edge in a rapidly evolving market.

Requirements

5+ years in Product Management (or equivalent experience) in B2B SaaS / enterprise software; experience with AI/ML products strongly preferred.
Located near Palo Alto and able to participate in customer meetings in-person when needed; comfortable being a visible product representative externally.
Strong business and GTM instincts: experience shaping strategy, packaging, and pricing; understands how products are sold and adopted in enterprise contexts.
Technical enough to collaborate effectively with engineers and AI teams—can discuss concepts like retrieval, embeddings, evaluation, hallucinations, latency, cost-to-serve, and deployment models without needing to be an ML researcher.
Track record of driving cross-functional alignment across Product/Engineering/Sales/Marketing with excellent written and verbal communication.
Comfortable operating in ambiguity: can create structure, prioritize ruthlessly, and keep teams moving without perfect information.

Nice To Haves

Familiarity with semiconductor / hardware-adjacent industries or enterprise buyers (e.g., manufacturing, defense, regulated industries).
Prior experience in competitive markets against modern AI startups, search, knowledge management, or enterprise platforms.

Responsibilities

Product Strategy & Execution: Lead priority initiatives from initial concept through to market delivery. You will align customer requirements and competitive trends with our long-term company goals.
Commercial Strategy: Own the evolution of our packaging and pricing models. You’ll define value metrics and tiering strategies that improve deal consistency and monetization.
Customer Engagement: Act as the product lead in key customer conversations and discovery sessions. You’ll validate our value proposition in real-time and communicate our product direction with authority.
Competitive Intelligence: Maintain an expert-level understanding of the AI landscape, especially around AI agents. You will turn these insights into actionable product decisions and sharper positioning for our sales team.
Cross-Functional Alignment: Serve as the primary point of coordination between Engineering, Sales, and Marketing. You will ensure that product launches are well-supported, internal stakeholders are aligned, and technical trade-offs are clearly understood by the business.
Technical Translation: Work closely with our AI and engineering teams to ensure our product remains enterprise-ready, focusing on critical factors like accuracy, security, and latency.