Fullstack Product Engineer

Ship AI-native product experiments that improve conversion and retention

We are hiring a Fullstack Product Engineer to own product experiments from user problem through production readback. Include “Product engineering is cool” in the subject line. Otherwise, your application will be disqualified.

You will work across the application stack, use AI as a serious development tool, and make product decisions with real user and business data. The role rewards fast learning and strong engineering judgment, not raw code volume.

About Single Grain

Single Grain is a revenue marketing agency. We build pipeline-focused systems that compound, not campaigns that expire. We have helped more than 500 companies, from venture-backed startups to the Fortune 500, drive measurable growth.

We operate as an AI-native team. Every role uses AI to improve speed, quality, judgment, and leverage. AI-generated code still requires sound architecture, testing, security, observability, and human review.

Your mission

Build and improve products that create customer value and convert more users into retained, paying customers.

Primary KPI: increase trial-to-paid conversion from the current baseline toward 40%, while maintaining product quality and learning velocity. By month six, the target operating cadence is at least two meaningful product experiments per month.

What you will own

• Turn user problems and product hypotheses into scoped experiments.

• Build production features across the front end, back end, data layer, and integrations.

• Define instrumentation before launch and read the result after launch.

• Improve activation, conversion, retention, reliability, and developer speed.

• Use AI for exploration, implementation, tests, debugging, and documentation with explicit QA.

• Make practical architecture and security tradeoffs, then document them.

• Speak with users and partner with growth, design, and operations when the product needs context.

What success looks like

In 30 days, you understand the product, users, stack, and baseline funnel, and you ship a production improvement.

By 60 days, you own a full experiment from problem definition through measurement and can explain the result.

By 90 days, you run a reliable experiment cadence and have improved a meaningful activation, conversion, retention, or reliability metric.

Evidence we need to see

• Two production products or features with your exact scope and technical ownership.

• One product or growth experiment with a measured result.

• A clear example of an architecture, reliability, security, or incident tradeoff.

• A concrete AI development workflow, including tests and human review.

• Evidence that you can move from an ambiguous user problem to a stable production result.

This role is not

• A ticket-only implementation role.

• A role for shipping AI-generated code without tests or review.

• A research-only seat with no production ownership.

• A role that optimizes speed while ignoring users, reliability, or measurable outcomes.

How the process works

1. Application and evidence review.

2. A focused product and engineering screen.

3. The published Beat Claude engineering challenge.

4. A live review of your solution, tradeoffs, and validation plan.

5. References and final decision.

Work model and compensation

This role is fully remote. State your location, time-zone overlap, start date, and compensation expectations. Current benefits listed for the role will be preserved after employment type is confirmed.

Originally posted on Himalayas