Engineering Manager, Patient Experience & Care Mode

Fullscript; Toronto; On-site; CAD 150,000 - 190,000; Full time

Benefits offered by this job

Generous PTO

RRSP match

Flexible benefits package

Training budget

Employee product discounts

Work Wherever You Work Well

Job summary

Fullscript is seeking an Engineering Manager to lead the Patient Experience pod and shape the technical and product foundations of Care Mode. You will blend engineering leadership, product thinking, and people management while staying close to the work—designing, implementing, and guiding decisions that impact both users and clinicians.

You’ll build systems that connect clinical data, behavioral signals, and real-world patient context, while raising the bar for reliability and user trust.

Qualifications

• Experience leading software products end-to-end.
• Deep engineering leadership with hands-on capability.
• Own difficult technical problems with product impact.
• Comfort moving between code and leadership.
• Strong technical judgment and explain decisions.
• Experience with high-scale apps and reliability.
• Product instincts linking engineering to user experience.

Responsibilities

• Lead patient experience engineering efforts and set technical direction.
• Stay hands-on through system design, reviews, and prototyping.
• Evolve architecture to support Care Mode and patient experiences.
• Collaborate with Product, Design, Clinical, and Data teams.

Skills

Engineering leadership

Software product ownership

Hands-on coding

React

React Native

Rails

GraphQL

Apollo

AI-assisted engineering

Systems thinking

Tools

Rails

GraphQL

Apollo

Job description

Fullscript is seeking an Engineering Manager to lead the Patient Experience pod and shape the technical and product foundations of Care Mode. You will blend engineering leadership, product thinking, and people management while staying close to the work—designing, implementing, and guiding decisions that impact both users and clinicians.

You’ll build systems that connect clinical data, behavioral signals, and real-world patient context, while raising the bar for reliability and user trust.