Engineering Tech Lead

Description:

About Legit Security

We're a well-funded cybersecurity company backed by top-tier VCs, solving one of the hardest problems in modern software security: how AI-first organizations can ship fast without security slowing them down. We're building the platform that secures the era where AI writes the code, using AI agents to generate secure code, detect vulnerabilities, and remediate them automatically. It's a fast-moving, category-defining space, and we're leading it.

The Role

You'll be the tech lead of a team of 6 engineers that builds the most technical and complex parts of our platform and runs them at large scale. This is a hands-on technical leadership role: you own the technical direction and the architecture, and you bring real passion for leading people and helping the engineers around you grow professionally. You lead through design docs, code review, and example, and you stay deep in the code.

We're looking for someone who has architected systems, shipped to production at scale, and led projects from idea to production, not just implemented someone else's spec. AI is both how you work and what you build: you use it to move faster every day, and you know what it takes to put LLMs in front of customers.

Our stack: Go, Python, and C#/.NET on the backend, React/TypeScript on the frontend, PostgreSQL and RabbitMQ, Kubernetes on AWS.

What you'll do

• Own the technical direction of your team and the technical quality of what it ships.
• Lead the design of the platform's most complex, multi-component systems: make the hard trade-offs, write the design docs, and drive them through review.
• Design and ship LLM-powered capabilities end to end: agent architectures, evaluation, guardrails, and the cost, latency, and reliability trade-offs of running them at production scale.
• Run what you build: share the team's on-call rotation, like every engineer here, and feed what production teaches you back into the design.
• Turn ambiguous, large-scope problems (most of them involving LLMs and agents) into concrete, shippable plans, and keep scope honest so the team ships predictably.
• Grow the engineers around you through code review, mentorship, and direct feedback: you raise the bar by example, not authority.
• Make AI-first engineering practice real for your team: not tool tourism, but everyday productivity.

• 5+ years of professional software engineering experience, including shipping and operating production systems at a commercial product company.
• 2+ years leading major projects or mentoring engineers, formally or informally: people have looked to you for direction, and you've raised a team's bar.
• A track record of independent technical leadership: you've personally architected systems, written the design docs, and led projects from idea to production.
• Hands-on experience operating high-scale production systems: performance, reliability, and cost trade-offs are not theoretical for you.
• Strong proficiency in a modern backend language and comfort working across the stack, including a modern frontend framework.
• You've built with LLMs, and AI tooling is core to how you build software: you can speak concretely about agent architectures, evaluation, where models fail, and how to design products that use them responsibly.
• Experience running services on Kubernetes in a major cloud - Advantage.
• Startup experience as a founder, core engineer, or first tech lead - Advantage.
• Experience building security products - Advantage.