- Location
- Toronto, ON
- Workplace
- Hybrid
- Type
- Full-time
- Department
- Engineering
- Source
- RecruiterFlow
Description
The client is a digital healthcare start-up on a mission to transform hospital care with AI. They provide hospitals with an end-to-end clinical AI solution that delivers better patient outcomes, reduced stress on staff and improved access to care. The platform provides model lifecycle management, including model development, deployment, monitoring, and operations, at a large scale.
As a Forward Deployed Engineer, you own the implementation of the client's platform inside a partner health system end to end. You'll embed with their teams, connect to their secure data systems, learn how their AI models and clinical workflows actually work, and build the monitoring and governance that fits them, including bespoke monitors when the standard ones don't.
You'll work closely with hospital stakeholders to earn their trust, understand their problems more deeply than they've articulated them, and spot the opportunities worth building for. What you learn in the field flows back to the platform: the patterns you surface and the tooling you build make our platform better for every partner. Reliability and correctness aren't
features here; they're the job. In healthcare the consequences of failure are categorically different - you'll work at the point where AI safety stops being theoretical and starts being a patient outcome.
Client has a hybrid office arrangement. You will be required to come into the office in downtown Toronto (walking distance from Bay Station) twice a week.
Key Responsibilities:
- Lead the deployment of AI platform and solutions across multiple health systems
- Understand the AI use cases deployed across a health system — predictive, generative, and agentic — recommend the key metrics to monitor for each, and onboard them to AIMS
- Coordinate across multiple stakeholders and drive alignment to onboard applications end to end
- Work both autonomously and collaboratively with Data, Governance, ML, and Engineering teams — across partner health systems
- Turn recurring patterns from the field into reusable building blocks, feeding what you learn back into the platform so each deployment makes the next one faster
Required Qualifications:
- Experience delivering complex AI systems in production or customer-facing settings
- Hands-on experience building LLM-based systems
- Solid backend development skills, with strong programming experience in Python, Java, or similar
- Excellent problem-solving skills and comfort working independently in fast-paced environments
- Highly client-facing, with excellent communication skills and a proven ability to build and grow strong client relationships — including with non-technical stakeholders across business and hospital teams
Preferred Qualifications:
- Direct experience with healthcare data and regulated environments (HIPAA, PHI, on-prem or air-gapped deployments).
- Background in clinical informatics or health-tech.
Benefits:
- Competitive compensation and stock options
- Entrepreneurial and energetic culture
- Excellent health and extended health coverage
- Four weeks of paid vacation
- Building impactful AI products and services that will transform hospital care!