Engineering Manager, Applied AI

2 нед. назад

от 0.075СШАLeadHybrid

ai systemsarchitecture reviewteam managementtechnical leadership

Manage and lead a team of AI engineers working on enterprise production AI systems, providing technical leadership and coaching.

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.
High trust, high agency, low ego. We push back when something isn't right and share what we learn, so good instincts spread fast.
We are our first client. We built Friday, our coding agent, and Statum, our knowledge infrastructure, and we run them on ourselves.
AI-first, human-accountable. Agents write nearly all our client code. Every output is reviewed, and the person is accountable.
Partners, not a vendor. You're in the room when hard calls get made, and you're expected to have a point of view.
Breadth that compounds. You'll see more industries and problems in a year than most people see in a career.
Weekends are yours. Pay is transparent, and we don't confuse long hours with good work.

Your engineers. Manage engineers up to senior, hold a high bar, and give direct, actionable feedback. Coach on execution and help strong engineers step up toward tech lead.
Technical leadership. Review architecture, agent, prompt, and eval design on your engagements. Step into hard technical and client situations, like production regressions and unclear requirements, and make the call. Raise trouble early, while it's cheap to fix.
Engagement delivery. Run the engagement-level relationship with clients and their stakeholders, alongside product and client partners, so each engagement lands.
Staffing. Manage transitions on your team, plan ahead, and flag risks before they reach a client. Escalate conflicts across engagements to the Head of Engineering.
Hiring. Interview, calibrate, close, and onboard new engineers against the bar the Head of Engineering sets.
Practice. Follow the team's practices and tell us what isn't working. Bring patterns you see to the wider team so they can become standing practice, and make sure your engineers use what exists.

3+ years managing engineers, with real experience giving feedback and developing people.
5+ 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.
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.
Bonus: management experience in a consulting, services, or forward deployed engineering organization, or experience taking a team or practice from zero to one.

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 partner. Most of your time stays on a client engagement, hands-on, close to the work and to where engineers get stuck. You'll manage a group of engineers across a few engagements and grow with the team as we do.
Level: Reports to the Head of Engineering. You run a team inside our system: you apply the bar, keep your engineers growing, and stay close to the work.
Base salary of $285,000 USD plus competitive equity
401k with 4.5% employer match, and fully covered medical, dental, and vision premiums
Monthly wellness stipend, Citi Bike, and pre-tax commuter benefits
12 weeks parental leave, with an optional 4-week ramp-up at 50%
Loft office in Soho with lunch and snacks
Hybrid in NYC. We're open to fully remote candidates in the US or Canada.

Initial screen (30 min): with our recruiting partner.
Technical screen (30 min): a short, real-world coding exercise with an engineer.
Hiring manager interview (45 min): behavioral and past work.
Technical interviews (2.5 hrs, two sessions): coding and systems design. Use AI tools in the coding interview, since it reflects how we work.
Case study (75 min): a live, scenario-based discussion covering staffing, feedback, technical review, and closing the loop. No prep needed.