What you’ll own

• Delivery: Planning, scoping, and shipping quality software against a roadmap you help shape. You make tradeoffs explicit and push back when we’re asking the team to do more than it can do well.
• How the team works: Enough structure to make delivery predictable, not so much that it slows a small team down. You remove friction, address recurring blockers, and improve how we use AI tooling.
• People: Hiring, clear expectations, regular feedback, growth, promotions, and exits when they’re necessary.
• Technical judgment: Staying close enough to the code and architecture to challenge decisions and support engineers without becoming the approval gate for everything.
• The engineering response to escalations: Getting the right people involved, making priority calls, and addressing recurring causes across customer, services-team, and open-source issues. You’re accountable for the response, not expected to personally fix every problem.

What we’re building

• A ground-up rebuild of the annotation editor, with interfaces generated by coding agents instead of hand-configured.
• Native evaluation of agent trajectories: trace ingestion, replay, and hybrid human-plus-model-judge workflows.
• Continuous calibration: treating automated evaluators as instruments that can drift and need ongoing checks against human ground truth.
• The workforce platform behind our managed services business.
• Quality analytics across annotators, models, and programs.
• Our own services team uses the platform to deliver customer work. You’ll see directly where the software helps, where it falls short, and which problems keep coming back. Part of the opportunity is turning that experience into better products, not just a growing list of one-off customer fixes.

Stack: Python/Django, TypeScript/React, Postgres, Kubernetes. Coding agents are part of how we work every day.

What success looks like

• Engineers take greater ownership and need less intervention.
• Scope and delivery risks surface early, rather than at the deadline.
• Customer commitments and product priorities are reconciled before they become emergencies.
• Recurring escalations lead to lasting fixes.
• The team ships more reliably, people are getting better at their work, and neither depends on you repeatedly stepping in to rescue a release.

Who we’re looking for

• You’ve managed engineers for at least a couple of years. You’ve hired and developed people, addressed underperformance directly, and made difficult people decisions when necessary.
• Before that, you were a strong engineer for long enough to develop sound technical judgment. You can reason about architecture and tradeoffs beyond your own code. You still build software and enjoy it.
• You use coding agents seriously and can explain, with examples, what effective use looks like.
• You’ve shipped at a startup and know how to make decisions with incomplete information.
• You say what you think early, give specific feedback, and don’t manage by avoidance.
• You can balance long-term product work with customer deadlines, negotiate realistic commitments, and recognize when a services request should become a product capability, and when it shouldn’t.
• Nice to have: experience with ML tooling, data platforms, or evaluation systems; experience managing a distributed team; frontend architecture depth.

How to apply

Skip the form. Email me directly at michael@humansignal.com with examples of your best work. That can be code you’ve written, a system you designed, a team you built, a document that changed a decision, or a product you shipped. I want to see what you’re proud of and hear why. You don’t need a public portfolio, and please don’t share proprietary material. A description of the problem, your contribution, and the outcome is enough. A short note on what draws you to HumanSignal specifically helps too. I read everything that comes in. If it’s a fit, I’ll reach out.