Senior / Staff Product Engineer, AINorth AmericaLearn more→

Linear
RemotePosted 7 April 2026

Job Description

Skip to content → Product Resources Customers Pricing Contact Log in Sign up Careers / Engineering Senior / Staff Product Engineer, AI Full-time (North America) Apply At Linear, we're building the product development system for teams and agents. AI is fundamentally changing how software gets built, and we’re shaping the tools this new era requires. Founded in 2019, Linear has become the platform of choice for more than 25,000 companies (including OpenAI, Coinbase, and Ramp) to plan, build, and ship their products. Today, our team is distributed across North America and Europe, and we’re continuing to grow internationally. What unites us is relentless focus, fast execution, and a deep care for software craftsmanship. We’re looking for experienced engineers who have shipped applied AI systems to production and want to define what the agent-native future looks like. We are building intelligence into the core of Linear, enabling the product to orchestrate coding, proactively move work forward, and power-up every software team. You’ll work closely with product and design to transform foundation models into structured, reliable workflows embedded deeply in the core of Linear. We care deeply about keeping Linear fast, intuitive, and opinionated—AI is no exception. Location & work mode Linear is a remote-first company. This role is open to candidates based in the North America. You can work from anywhere within this region. We value deep focus and async collaboration, with intentional moments to connect in person through team off-sites, optional co-working, and occasional travel. What you'll do Build AI-powered product features that feel native, fast, and delightful to use Work with product and design to prototype and iterate on intelligent workflows and user interactions Design backend services to power natural language interfaces, smart suggestions, agentic workloads, and more Optimize prompts, fine-tune model behavior, and evaluate performance Help to guide our agent platform, allowing third parties to bring agents into the core Linear experience as teammates. Contribute to the architecture for AI-integration infrastructure that’s reliable and privacy-aware Our tech This stack reflects the systems we build and operate. You’re not expected to have experience with everything listed, but you should be excited to work close to product, performance, and real-world scale. Pluggable agentic workload system utilizing temporal, operating at production scale Proprietary websocket data sync framework built for speed and offline support React, MobX, styled-components on the frontend Extensive, widely used, GraphQL API and SDK Node, Postgres, Temporal, and Redis in the backend Hosted on Google Cloud with k8s GitHub, Slack, Notion What we offer We're a small, focused team that cares deeply about the quality of our work and the people we do it with. Here's what you can expect: Competitive salary and equity Employee-friendly equity terms including early exercise in the US and extended exercise windows Daily meal and coffee stipend on every workday Paid co-working space or desk Health coverage (based on country requirements) 5 weeks paid vacation, plus local statutory holidays 4 months paid parental leave Paid month off after 4 years & every 2 years thereafter Regular team events and off-sites Remote-first with no required commute Learn how we think and work Read Me a story about our mission How we work: Designing remote work at Linear Why and how we do work trials Linear blog post Crafting quality that endures Config keynote by our Co-founder & CEO, Karri Saarinen How we structure our product teams talk by our Head of Product, Nan Yu, at Config 2024 Scaling our real-time sync engine talk by our cofounder, Tuomas Artman, at Linear's 2023 offsite First Round Capital: The Unsung Ingredient: Taste Linear is an equal opportunity employer. We do not discriminate based on race, color, religion, gender identity o ... (truncated, view full listing at source)
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