Principal Product Builder, Agent Analytics & Optimization

Conviva•Foster City, CA

About The Position

This is a Next Generation PM Role. AI has fundamentally changed what it means to build software. The best product people no longer just write specs and hand them off—they prototype, ship, and iterate with AI-powered tools at a pace that was unimaginable two years ago. We're looking for someone who has already crossed that line: a product leader who builds, not just plans. Conviva is the intelligence layer for digital businesses, turning every consumer interaction into outcome-based intelligence—linking engagement patterns across AI agents, apps, websites, and streaming video to real results such as purchases, bookings, and resolved support requests. Powered by its patented Time-State Technology®, the Conviva® Operational Data Platform delivers real-time insights and automation that help leading enterprises grow, improve satisfaction, and build lasting trust. The Opportunity AI agents are quickly becoming a new "digital surface" alongside mobile and web. But teams still struggle to answer basic questions: Are my agents working and achieving outcomes? What drives success? How do we optimize behavior, reliability, and user outcomes? How do I launch an agent and have it continuously adapting to the ever-changing world? Conviva has an industry-leading answer to these questions. This role is a chance to define and lead a brand-new category: analytics and optimization for AI agent experiences, backed by strong platform foundations, real customer problems, and a track record of disruptive innovation. You won't just manage this product—you'll build it. You'll use AI coding tools to prototype features, validate ideas with working software, and move from insight to artifact faster than any traditional product process allows. You'll work at the intersection of product strategy and hands-on creation, partnering with engineering, design, and go-to-market to ship quickly, learn constantly, and set the direction for where agent analytics goes next. Why "Product Builder" and Not "Product Manager" The rise of AI-assisted development has created a new kind of product professional—one who can go from customer insight to working prototype in hours, not weeks. We call this role a Product Builder because: Build to think: Instead of writing a 20-page spec, you spin up a working prototype to test your hypothesis. Your artifacts are software, not slide decks. AI-native workflow: You use AI coding tools as a force multiplier—not to replace engineers, but to close the gap between "idea" and "something customers can react to." End-to-end ownership: You own the product from strategy through execution. You don't toss requirements over the wall; you're in the code, in the data, and in front of the customer. Still a product leader: This is a PM-first role with builder superpowers. You lead product strategy, customer discovery, and prioritization—and you also ship. What Success Looks Like Product Vision & Strategy

Requirements

5–10+ years in product management, with meaningful experience in analytics, data platforms, developer tools, or AI/ML products.
Energized by 0→1 ambiguity and can turn fuzzy problems into crisp product direction.
Customer-obsessed but practical—deep empathy plus strong prioritization.
Communicate clearly in writing and in live discussions. Can zoom out (strategy) and zoom in (details) without getting stuck in either.
Build alignment fast and keep teams moving.
Actively use AI-assisted development tools (e.g., Cursor, Claude Code, GitHub Copilot, Replit, v0) to build prototypes, internal tools, or production-adjacent artifacts. Show us what you've built.
Comfortable reading and modifying code (Python, JavaScript/TypeScript, SQL, or similar). You don't need to be a senior engineer—but you can't be code-averse.
Engineering background, CS degree, or equivalent hands-on technical experience is strongly preferred.
Experience with or strong interest in: LLM application development, agentic systems, RAG architectures, prompt engineering, or AI evaluation frameworks.
Have shipped something you personally built (side project, internal tool, prototype, open-source contribution)—not just managed the backlog for.

Nice To Haves

Experience in digital experience analytics, observability, or APM.
Familiarity with conversation analytics, agent evaluation, or LLM-ops tooling.
Published writing, talks, or open-source work demonstrating thought leadership at the intersection of product and AI.
Experience building with AI agent frameworks (LangChain, CrewAI, AutoGen, etc.).

Responsibilities

Own product outcomes: defining vision, strategy, roadmap, and success metrics.
Discover and define the category: talk to customers weekly, map workflows, validate problems, and translate insights into sharp product bets.
Turn ambiguous, fast-moving market signals into clear product direction with strong conviction.
Use AI development tools (Cursor, Claude Code, Windsurf, Replit, v0, etc.) to rapidly prototype concepts, validate UX hypotheses, and create working demos that accelerate team alignment and customer feedback.
Partner deeply with engineering, design, and data/ML to ship high-quality product experiences from concept to launch to iteration.
Create internal tools, dashboards, and proof-of-concept applications that solve immediate team or customer needs.
Drive execution: prioritize ruthlessly, unblock teams, manage tradeoffs, and ensure timely delivery.
Bridge the gap between product thinking and technical implementation—you should be equally comfortable in a customer interview and reviewing a system architecture.
Contribute to a culture where building is the default mode of exploration, not just analysis and documentation.