Engineering Team Lead - AI-Driven Full-Stack Leader

STAN AI; Toronto; On-site; Confidential; Full time

Benefits offered by this job

Competitive salary

Health benefits

Macbook provided

Free parking

In‑office restaurant

Building-wide perks

Unlimited ping pong

Job summary

STAN AI is seeking an Engineering Team Lead to guide a small, high-impact full-stack squad within our growing 11-person engineering team. You will code alongside 2–3 engineers, run sprints, mentor, and drive architecture decisions while helping hire the talent that will shape the team and product.

You will report to the Director of Engineering, collaborate with product, and influence how we build and deploy AI in our workflows.

Qualifications

• 5+ years of software engineering experience with 1–2 years in a tech lead capacity.
• Strong full-stack skills in Node.js and TypeScript (frontend and backend).
• Experience mentoring engineers and owning features end to end.
• Excellent communication to explain decisions to engineers and non-engineers.
• Thrives in fast-moving startup environments with shifting priorities.

Responsibilities

• Define the squad's technical direction, architecture decisions, and coding standards.
• Lead sprint planning, retrospectives, and mentor 2–3 engineers.
• Collaborate with product/design to translate requirements into work.
• Champion AI tooling adoption (Claude Code) and integrate AI into workflows.
• Own delivery estimates, risks, and engineering processes as the team scales.

Skills

Node.js

TypeScript

Full-stack

Leadership

Mentoring

Architecture

Communication

Hiring

Tools

Claude Code

Copilot

Cursor

LLMs

Job description

STAN AI is seeking an Engineering Team Lead to guide a small, high-impact full-stack squad within our growing 11-person engineering team. You will code alongside 2–3 engineers, run sprints, mentor, and drive architecture decisions while helping hire the talent that will shape the team and product.

You will report to the Director of Engineering, collaborate with product, and influence how we build and deploy AI in our workflows.