Engineering Team Lead, Management Track

You are a tech lead who is ready to move toward management, or already partway there. You will lead a team of two to three other engineers, depending on the team, reporting to the Engineering Manager and working closely with the Principal Architect (who holds architecture sign-off) and the Product team.

The split is roughly 25 to 50 percent hands-on development and 50 to 75 percent leading people and coordinating work. The person in this role knows the tech stack and the business well enough to make good calls, and either has people-management skills already or is clearly ready to develop them.

We are hiring two people for this role. Each will take on a share of the team-facing work that currently sits with the Engineering Manager.

• You are serious about KATIX specifically. You have looked at the product, you understand what we are trying to do for people selling a vehicle, and you have a concrete reason to want to lead a team doing it here. We ask about this in every interview, and for this role we expect a clear answer.

• You have changed how a team works with AI, not only how you work. Personal productivity with AI is table stakes. For this role we want evidence at the team or organization level: you introduced AI-assisted development to a team, set verification standards, built internal tooling or agents, and can describe what it did to the team’s output. We look at this directly in the interviews.

In this position you’ll be able to choose a track: Engineering Manager as the department grows, or the specialist track if you find the architecture and platform side is where you want to stay. Both paths are real and both are open to you. You choose your track.

Responsibilities

• People
  • Regular 1on1s with each engineer on your team
  • Setting and scoring goals for your team that tie to company KPIs, and contributing to evaluations
  • Growth plans for each engineer, including developing your team’s next tech lead
  • Onboarding new hires and interns
• Delivery
  • The team’s Kanban flow: planning, daily standups, retrospectives
  • Removing blockers and keeping work moving from input to production
  • Delivery metrics (lead time, review delay, deploy frequency) and acting on what they show
• Business
  • Translating company KPIs (listing rate, closing rate, lead time to listing, transaction volume) into your team’s goals
  • Reporting progress upward weekly, in terms of outcomes rather than tickets
• Cross-department
  • Working directly with Customer Success, Sales, Promotion, and Corporate, in Japanese, on requirements, expectations, and delivery
  • Supporting other departments as they build with AI, so they can ship safely without a queue into engineering
• AI-native practice
  • Setting and holding the team’s standards for AI-assisted development: how work is decomposed, how AI output is verified, how AI-generated code is reviewed
  • Measuring the effect on the team’s delivery and adjusting
• Hiring
  • Casual interviews, first interviews, and evaluating technical exercises for your team’s open roles
• Reliability
  • Coordinating incidents that touch your team’s systems, running blameless postmortems, and seeing follow-through to completion
• Standards
  • Contributing to engineering-wide standards: review culture, the team’s Code of Conduct, AI usage guidelines
• Hands-on
  • Code review, architecture input, unblocking, and building features when the team needs it

Requirements

• 5 or more years of professional web engineering, including at least one to two years as a tech lead or equivalent, leading a team of three or more engineers
• Full stack background in a modern web stack. You can review, unblock, and contribute in Next.js and TypeScript, and you are not put off by a Rails legacy on the bike side
• Japanese at JLPT N2 or higher. This is a hard requirement. You will lead team members who do not speak English, collaborate with non-engineering departments, and take part in meetings conducted in Japanese. It does not need to be perfect. It does need to work reliably above casual-conversation level.

Nice to haves

While not specifically required, tell us if you have any of the following.

• A track record of growing engineers: people you mentored who took on more, or a team whose output improved under you
• Led AI adoption at team level with outcomes you can describe
• Business fluency: you can explain how engineering work you led moved a business metric, and you are comfortable being measured that way
• Comfortable running 1on1s, giving direct and kind feedback, and facilitating a team’s working rhythm
• Prior people-management responsibility, including hiring or evaluations
• Incident management and postmortem experience
• Kanban or flow-metrics experience
• Observability and SLO work (Sentry, New Relic)
• Marketplace, e-commerce, auction, or escrow-adjacent product experience
• Experience helping non-engineers build or automate with AI