AI Engineer/Architect

Abbott; Toronto; On-site; CAD 120,000 - 180,000; Full time

Job summary

A leading company focused on diabetes management seeks an AI Engineer/Architect to drive GenAI solutions. This role combines hands-on development with strategy, involving LLM APIs, design of scalable systems, and consulting across teams to ensure effective AI integration.

Qualifications

• 10+ years of experience for Bachelor's Degree or 7+ years for Master's.
• 4–8 years developing AI/LLM solutions.
• Experience in regulated industries is a plus.

Responsibilities

• Build and integrate AI solutions using LLM APIs.
• Design scalable APIs for AI-driven features.
• Drive tactical execution of AI initiatives across products.

Skills

Python development

AI architecture

Cloud-based LLMs

Testing and Debugging

Communication

Education

Bachelor's Degree or Master's Degree

Job description

At Abbott, we believe people with diabetes should be empowered to enjoy healthy and happy lives. That’s why we’re focused on helping people with diabetes manage their health more effectively and comfortably, with life-changing products that provide accurate data to drive better-informed decisions. We’re revolutionizing the way people monitor their glucose levels with our new sensing technology.

Our Diabetes division currently has an opportunity for a hands-on AI Engineer / Architect who will drive the design, development, and implementation of GenAI solutions across our products and teams.This isn't just an architecture role — you’ll build, code, integrate, optimize, and lead, working directly with LLMs, APIs, and AI pipelines.#software

What You'll Do

Build and Integrate AI Solutions using LLM APIs (OpenAI, AWS Bedrock, Anthropic, Mistral) — not just plan, but hands-on develop.

Shape LLM behavior through prompt engineering, guardrail development, and fine-tuning pipelines.

Design and build scalable APIs (e.g., FastAPI, Flask) to enable AI-driven features across products.

Lead performance tuning and ensure system scalability across mobile and cloud platforms.

Implement GenAI Safety Best Practices , focusing on hallucination mitigation and secure model usage.

Estimate and optimize costs for large-scale cloud LLM operations (10–20M / year scale).

Consult and Communicate AI strategies to legal, compliance, quality, and executive teams — tailoring technical concepts to diverse audiences.

Own and Drive Tactical Execution of AI initiatives across multiple products, not just providing oversight.

Required Qualifications

Bachelor's Degree with 10+ years of experience or Master's Degree with 7+ years of related software architecture experience (not all AI related) across mobile and cloud platforms.

4–8 years of hands-on experience developing and implementing AI / LLM architecture and solutions. (.)

Strong Python development skills— building new APIs, integrating LLMs, and engineering GenAI applications.

Deep experience working with cloud-based LLMs (e.g., OpenAI, AWS Bedrock, Anthropic, Mistral models).

Testing and Debugging—proficiency in AI app testing techniques, including unit testing, integration testing, and UI testing across various mobile devices and operating system platforms.

Strong communication and documentation skills— producing diagrams, demos, and technical artifacts that make AI strategies understandable and actionable.

Proven ability to design for cost efficiency and scalability.

Strategic thinker who balances technical innovation with business needs.

Preferred Qualifications

Experience developing GenAI agents and LLM meshes.

Background in large enterprise architecture or scaling AI solutions across multiple business units.

Experience working in or around regulated industries (healthcare, life sciences, finance) is a plus.