Founding Engineer, Platform & Applied AI

Kintaro Labs; New York (NY); On-site; USD 120,000 - 200,000; Full time

Job summary

Kintaro Labs, a New York technology company building autonomous systems, is seeking its first engineering hire to own the platform and apply AI across products. You will design, implement and maintain the infrastructure that runs user code, while advancing AI-driven features with safety and scalability in mind.

You will balance reliability, security and cost, mentor interns and later engineers, and help shape engineering standards as the team grows from a hands-on core into a scalable

Qualifications

• Strong in at least one programming language and quick to pick up others.

Responsibilities

• Own the platform our products run on, including isolation sandbox, reliability and cost.
• Lead architecture decisions: hosting provider, scaling to more users, and cost per user.
• Design and run AI engineering workflow: briefing, testing, reviewing and merging coding agents.

Skills

Python

Go

TypeScript

Job description

Kintaro Labs is a New York technology company building autonomous systems: planning, acting, and improving on their own. We build the same way: a very small team directing AI agents that write most of our code.

About the role

You will be the first engineering hire, with two responsibilities. The first is the platform: the infrastructure our products run on, and its reliability, security and cost. The second is applied AI: how we build software with coding agents, and how AI features reach production safely. You will write code yourself in both. How much of this you lead from day one depends on what you bring.

What you will do

Platform

• Own the platform our products run on, including the service that creates, pauses, wakes and recovers an isolated compute environment for every user.
• Own reliability in production: monitoring, incident response, backups and restore drills. Share on-call with the founders.
• Lead architecture decisions: hosting provider, cost per user, and how the system scales to ten times the users.
• Harden the sandbox that runs user-written code, and the limits on compute and AI spend.

Applied AI

• Design and run our AI engineering workflow: how coding agents are briefed, tested, reviewed and merged, and how we measure whether their output is correct.
• Build AI features in our products: agents that plan, use tools and coordinate with each other, with evaluation, cost and speed controls.
• Evaluate new models and tools as they are released and decide what we adopt.

Across both

• Write production code yourself on the hardest parts of our systems.
• Set and enforce engineering standards: code review, automated testing, releases, security and data handling.
• Help hire and mentor interns and later engineers.

About you

We do not hire on years of experience. You may be early in your career or well into it. What matters is what you have built, how you think and how you work.

• You have built something real and kept it running: a product, a service, a research system or a serious personal project. Scale matters less than having owned it.
• You take ownership. Given an unclear goal, you work out what is needed, get it done without being chased, and say plainly what you found.
• You want to commit to this company and help build it from the start.
• You solve problems from first principles and adapt quickly as the tools change.
• Strong in at least one programming language and quick to pick up others. Our current stack uses Python, Go and TypeScript.
• You have built on top of large language models, such as an agent, a tool-using assistant or an evaluation system, and can explain how you tested it and where it failed.
• You use AI coding agents every day and have a clear view of where they can and cannot be trusted.
• You care about doing things properly: testing, review, security, and understanding why something works before you ship it.
• You can explain technical trade-offs to non-engineers and turn incomplete requirements into small working iterations.

Useful exposure (optional)

Cloud infrastructure (AWS or similar), containers or microVMs, running untrusted code in sandboxes, databases and backups, model gateways and cost controls, evaluation frameworks, open-weight or local models, trading or market-data systems.

Compensation

Salary and equity, matched to what you bring.

Kintaro Labs, Inc. is an equal opportunity employer.