Productboard

HQ
San Francisco
Total Offices: 5
246 Total Employees
112 Product + Tech Employees
Year Founded: 2014

Productboard Benefits Overview

Compensation + Benefits

Offers 401(K)

Offers company equity

Offers dental insurance

Offers vision insurance

Offers health insurance

Offers mental health benefits

Offers generous parental leave

Provides fertility benefits

Career Growth + Development

Provides customized development tracks

Work-Life Balance + Wellbeing

Offers generous PTO

Provides paid holidays

Offers paid volunteer time

Provides paid sick days

Offers gym membership

Company Culture

Offers a remote work program

Provides free snacks and drinks

Recently posted jobs

3 Days AgoSaved
Remote or Hybrid
28 Locations
Artificial Intelligence • Information Technology • Productivity • Software • Analytics
Lead the AI architecture for Productboard Insights, designing agent-native systems, context infrastructure, self-healing workflows, evaluation processes, and AI code-review optimization. Own technical direction across Insights, Spark, and platform teams; drive features from concept through beta; optimize quality, latency, cost, and reliability; write production code; and develop engineers through documentation and reviews.
9 Days AgoSaved
Remote or Hybrid
28 Locations
Artificial Intelligence • Information Technology • Productivity • Software • Analytics
Own the architecture enabling AI-first product engineering, including agent-native standards, context infrastructure, self-healing incident workflows, autonomous agent features, and AI code review optimization. Ship full-stack product features, set technical direction, and partner with product and design teams. The role requires strong backend engineering, production LLM experience, distributed systems expertise, and practical use of AI coding tools.
9 Days AgoSaved
Remote or Hybrid
28 Locations
Artificial Intelligence • Information Technology • Productivity • Software • Analytics
Lead the architecture and implementation of AI-native product engineering systems, including agent-ready code standards, context infrastructure, self-healing incident workflows, multi-step agentic features, and AI code-review optimization. Ship end-to-end product features, set technical direction, evaluate LLM reliability and trade-offs, and accelerate validated learning through close collaboration with engineering, product, and design teams.