Product Engineer

Role Description

We are looking for a Product Engineer who owns products end to end — from problem to production to the metric that proves it worked — using AI as a force multiplier, not a novelty. This role exists because of how we build: a small product strategy team sets direction and priorities, and engineers own the work end to end — discovery, design, build, ship, and the result. You’ll have the autonomy of a founder inside your domain, and the accountability that comes with it.

This is a 100% remote/work-from-home role.

Key Responsibilities

• Own the full lifecycle of features and products across our consumer platform (e.g., Career.io, Resume.io and adjacent surfaces) — you are the product owner, designer, and engineer for your domain.
• Front end to back end to data.
• You build the UI, the services behind it, and the instrumentation that tells you whether it worked. No throwing work over a wall.
• Velocity with judgment.
• You ship continuously and safely, using AI tooling to compress the build loop without compromising quality, security, or maintainability.

You're Someone Who...

• Is AI-native by default.
• You already get meaningful leverage from agentic tools (Claude Code, Claude Design, and similar) and treat learning to use them better as part of the craft.
• Defines success up front in measurable terms, ships to production, watches the numbers, and iterates or kills based on what the data says.
• Focuses on outcome over output.
• Has high agency, low ceremony.
• You don’t wait to be told what to build next. You operate with founder-like ownership inside your area.
• Is Direct.
• You communicate crisply with strategy, design, and other engineers, and you push back when you think a direction is wrong.

Must-Haves

• Proven full-stack ability. You are genuinely comfortable across the stack — modern front end (TypeScript/React or equivalent) through backend services and data — and can ship a feature end to end without a handoff.
• A track record of shipping products end to end, ideally where you owned more than the code — scope, tradeoffs, and results.
• Demonstrable AI leverage. You can walk us through real work where AI tooling materially multiplied your throughput, and you have opinions about where it helps and where it doesn’t.
• Product judgment. You can take an ambiguous problem, decide what to build, and defend the call. You think about the user and the business, not just the implementation.
• Data fluency. You can define, instrument, and read your own metrics, and you let evidence change your mind.
• Speed and quality together. You move fast and leave behind systems you’d be happy to maintain.
• Authorization to work for any US employer.

Nice-to-Haves

• Familiarity with our domain (careers, hiring, resumes, marketplaces) or other high-traffic consumer products.
• Comfort with cloud-native infrastructure (AWS, Kubernetes, IaC) and modern data tooling.
• A public body of work — shipped products, open source, writing, or side projects that show what you do unprompted.