Staff AI Engineer
Socket.dev · Toronto, Canada ·
- Work mode
- Remote
- Seniority
- Staff
- Category
- AI engineering
- Experience
- 2+ years
- Company size
- 501-1000
- Salary
- CAD 170,000 – 180,000 / year
Socket.dev · Toronto, Canada ·
getmaple · Toronto, Ontario
Robots and Pencils · US Remote
getmaple · Toronto, Ontario
Cobaltotalent · Nuevo León, Mexico
Build and scale AI features for a healthcare platform, setting evaluation, safety, and agent-execution standards while coaching teams to ship compliant, high-quality AI safely.
Maple’s purpose is to meet the world's healthcare needs. We’re Canada's leading on-demand healthcare platform, connecting patients with Canadian-licensed doctors, nurse practitioners and specialists. Today, we’re proud that over 8 million patients and 7,000 businesses and government partners have access to same‑day, proactive and ongoing care. We enable people to take control of their health and push the boundaries of what’s possible every day.
Bold minds. Big impact. A career at Maple is about making an impact. We empower bold thinking, surround you with an inspiring team and are driven by a motivating purpose. Here, you’ll do work that changes lives—including your own.
We're looking for a Staff AI Engineer to help our engineering teams build, evaluate, and scale AI features across the product — and set the bar for what great looks like.
In this role, you'll design the evaluation, safety, and agent execution patterns that every squad builds to, stay hands‑on with reference implementations and evaluation harnesses, and coach engineers across the org so squads can ship AI features safely and confidently. You'll work closely with Product Engineering, Platform Engineering, Product and our Security, Privacy, and Clinical partners — turning a fast‑moving, regulated healthcare environment into a place where AI can scale with the quality patients and providers deserve.
In your first 90 days, you'll complete a landscape assessment of Maple's current AI features, evaluation coverage, cost profile, and governance gaps. You'll publish an initial AI standards and best‑practices guide covering prompt and agent design, evaluation expectations, safety and PHI handling, and cost hygiene — and stand up an initial evaluation strategy and reference harness that at least one product squad has adopted for an in‑flight feature. By month three, you'll have agreed on the ownership interface with Platform Engineering and built the working relationships across Product, Security, Privacy, and Clinical you'll rely on going forward.
Over your first 12–18 months, you'll roll out a company‑wide agent execution architecture adopted by the majority of squads shipping AI features, stand up production‑grade monitoring for quality, safety, cost, and latency with clear SLOs, and deliver measurable AI cost optimization against your v1 baseline. Every customer‑facing AI feature will be covered by an approved evaluation harness and monitoring dashboard, and squads will be independently shipping AI features to Maple's standards.
Finding the right fit goes both ways—so this section is yours to complete. When you join, you'll add the unique strengths you bring that aren't captured above.
We value strong architectural fundamentals and systems thinking over knowing every single tool in our stack, but here is what you will be working with:
We recognise our people's health is everything. That's why we take care of them.
Offers can vary depending on skills, experience and readiness to meet Maple's expectations for this level. We encourage open conversations about pay. If you have questions about how compensation works at Maple, you're welcome to ask at any point in the interview process.
We're committed to the safety and security of our platform. Please note that any offer of employment is subject to a criminal record check (EPIC) and identity verification. Additional checks, including employment or education verification, may be conducted depending on the role's requirements.
We don't currently use artificial intelligence (AI) or automated tools to screen, assess or select candidates. Every application is thoughtfully reviewed by our Talent Acquisition team or hiring managers.
Condé Nast · 1 World Trade Center, New York, NY