Senior Engineering Manager, Applied AI

Headstart•New York, NY

1d•$300,000 - $300,000•Hybrid

About The Position

Headstart is built for people who want to think like founders. We work inside real enterprises ($100M+ ARR), shipping production AI systems that change how they operate. Every engagement is a different industry, problem, and set of constraints. We're bootstrapped, cash-flow positive, and growing fast, and we're building our own platform to deliver truly agentic systems. Enterprise clients bring us messy, high-stakes problems, often with no clear picture of what the AI system should be. Our engineers work out what to build, build it, and run it in production. Most of the time, they're the experts in the room. This role is part player, part coach, part staffing lead, part hiring engine. You'll start on a client engagement to learn the work and where engineers get stuck. Then you'll build and lead a team and help shape the company as we grow.

Requirements

4+ years managing engineers, including senior and staff, with real experience hiring and developing them.
8+ years in software engineering, deep enough to review designs and challenge the team's approach.
Hands-on with Python.
Experience delivering software in real client environments and taking something from zero to one, whether a team, a practice, or a hiring process.
Curious about agents, evals, and multi-agent systems, with a sense of where they're reliable and where a person needs to take the wheel.
Fluent with AI coding tools.
Depth matters more than prior title.

Nice To Haves

Management experience in a consulting, services, or forward deployed engineering organization.

Responsibilities

Hold a high bar and grow each engineer through direct, actionable feedback.
Develop senior engineers into tech leads.
Give clear priorities and expectations without adding process before we understand the problem.
Review architecture, agent, prompt, and eval design.
Step into the hardest technical and client situations, like production regressions and unclear requirements, and make the call.
Raise trouble early, while it's cheap to fix.
Spot patterns across engagements and turn them into standing practice, reference implementations, and platform capabilities.
Check that the next engagement is faster because of it.
Shape who works on which engagement, plan transitions ahead, and flag risks before they reach a client.
Run hiring for your team, from sourcing to onboarding.
Define the hiring bar.
Work closely with product, client partners, and client stakeholders so each engagement lands.