Lead AI Delivery Engineer - Hybrid (In-Office 2 Days)

McKesson; Mississauga; On-site; CAD 120,000 - 170,000; Full time

Job summary

The US Oncology Network in Mississauga seeks a Lead Forward Deployed Engineer to partner with business teams and deliver AI-enabled solutions from discovery to prototype. You will understand workflows, frame problems, and prototype rapidly while guiding the path to production.

You will build working prototypes, coordinate with AI Application Engineering, Data Engineering, MLOps, and security teams, and mentor engineers to ensure governance and scalable outcomes.

Qualifications

• 8+ years of experience delivering enterprise software solutions.
• Hands-on full-stack engineering across web apps, APIs, data, AI services, security, and cloud infrastructure.
• Experience translating ambiguous business problems into working technical prototypes or proofs of concept.

Responsibilities

• Embed with business teams to understand workflows, user needs, and outcomes.
• Lead discovery, framing sessions, and define measurable success criteria with stakeholders.
• Build prototypes and proofs of concept; test with representative users for feasibility.
• Advise on AI, data, or workflow tech choices and communicate risks and tradeoffs.
• Handoff to engineering for production and ensure governance, security, and operational readiness.

Skills

8+ years enterprise software

Full-stack engineering

React, Node.js, TypeScript, Python

AI-enabled solution prototyping

Stakeholder engagement

Problem framing / solution design

Education

Bachelor's degree in Computer Science, Engineering, Information Systems

Tools

Snowflake

Databricks

Azure AI services

REST APIs

Job description

The US Oncology Network in Mississauga seeks a Lead Forward Deployed Engineer to partner with business teams and deliver AI-enabled solutions from discovery to prototype. You will understand workflows, frame problems, and prototype rapidly while guiding the path to production.

You will build working prototypes, coordinate with AI Application Engineering, Data Engineering, MLOps, and security teams, and mentor engineers to ensure governance and scalable outcomes.