We are looking for a hands-on Engineering Lead to drive the design and delivery of our security products. You will lead a small, cross-functional team of backend, frontend, and QA engineers, owning technical direction, code quality, and delivery outcomes while remaining actively involved in building. You will partner closely with the product to shape the roadmap and translate it into well-architected, secure, and reliable software. This is a player-coach role: roughly half technical leadership and architecture, half mentoring and delivery management.

AI-native development is essential to this role, not an add-on. We expect our Engineering Lead to drive the adoption of AI coding tools (such as Claude Code) across the entire development process, and to build the framework, standards, and guardrails that ensure the whole engineering team consistently follows it. The goal is to materially accelerate delivery while keeping quality high, and to make AI-assisted development a repeatable, measurable part of how the team works.

Technical Leadership:

• Own the technical architecture and design decisions for backend services, APIs, and integrations, balancing performance, scalability, security, and maintainability.

• Set and uphold engineering standards: coding conventions, code review practices, testing strategy, and CI/CD pipelines.

• Remain hands-on, contributing to critical features, complex problem areas, and proofs of concept in Python.

• Evaluate and adopt new technologies, tools, and best practices to continuously improve the team’s velocity and product quality.

AI-Native Development & Delivery Acceleration:

• Design and build a structured AI-native development framework — standards, workflows, prompt/context patterns, and review checkpoints — that the whole engineering team follows.

• Embed AI tooling across the full development process: scoping, code generation, testing, review, and documentation.

• Ensure consistent team adoption of the framework through enablement, coaching, and clear expectations, and iterate on it as tools evolve.

• Define and monitor quality guardrails for AI-assisted output, tracking metrics such as rework rate and change failure rate to prove delivery is faster without sacrificing quality.

People & Team Leadership:

• Lead, mentor, and grow a small cross-functional team of backend, frontend, and QA engineers.

• Foster a collaborative, accountable, and high-trust engineering culture.

Delivery & Execution:

• Translate product requirements into clear technical plans, milestones, and well- scoped work.

• Plan and manage delivery across monthly milestones, balancing scope, quality, and timelines.

• Identify and remove blockers, manage technical risk, and keep stakeholders informed on progress.

Cross-Functional Collaboration:

• Partner with product managers and stakeholders to shape the roadmap and define the scope for each release.

• Communicate technical concepts, trade-offs, and decisions clearly to both technical and non-technical audiences.