Job Description: At Sun Life, we're driven by our Purpose: helping our Clients achieve lifetime financial security and live healthier lives.

Our values shape how we work: caring, authentic, bold, inspiring, and impactful.

Corporate IT is seeking an experienced Lead AI Engineer to design, develop, deploy, and support enterprise-grade Artificial Intelligence, Machine Learning, and Generative AI solutions on AWS.

The successful candidate will combine strong software engineering capabilities with hands-on knowledge of AWS AI/ML and application services to build secure, scalable, observable, and production-ready solutions that drive measurable business value.

This role will collaborate with architects, product owners, data engineers, security and governance partners, and business stakeholders to deliver AI-powered applications, retrieval-augmented generation (RAG) solutions, intelligent agents, automation workflows, and reusable AI platform capabilities.

The ideal candidate has a proven record of taking complex software and AI solutions from design through production operations.

What will you do? Design, develop, test, deploy, and operate AI, Machine Learning, and Generative AI solutions using AWS services and approved enterprise architecture patterns.

Build production applications using foundation models through Amazon Bedrock, including prompt engineering, RAG, tool use, intelligent agents, and workflow automation.

Design secure RAG pipelines covering document ingestion, chunking, embeddings, indexing, retrieval, grounding, evaluation, and governance using Amazon S3 and approved vector-search technologies.

Engineer agentic solutions with controlled tool access, orchestration, state and memory, error handling, authorization, human approval points, and auditable execution.

Build scalable serverless and containerized services using AWS Lambda, Amazon API Gateway, AWS Step Functions, Amazon Event

Bridge, and, where appropriate, Amazon ECS or Amazon EKS.

Implement fit-for-purpose data and persistence patterns using Amazon S3, Amazon DynamoDB, Amazon Aurora or Amazon RDS, and AWS Glue.

Apply enterprise security and governance controls, including least-privilege AWS IAM, encryption with AWS KMS, secrets management, private connectivity, data protection, model guardrails, and auditable access patterns.





Implement automated evaluation, testing, monitoring, tracing, and cost controls for AI applications, including model and tool-call quality, latency, reliability, safety, and usage metrics.

Build CI/CD pipelines and infrastructure as code; contribute reusable components, engineering standards, automated quality gates, security guardrails, and operational runbooks.

Create and maintain technical design artifacts covering application functionality, architecture, data flows, interfaces, integrations, security controls, and operational requirements.

Provide post-production support, troubleshoot complex issues, optimize performance and cost, and continuously improve deployed solutions.

Collaborate effectively in an Agile environment, communicate technical trade-offs clearly, and mentor junior team members.

What do you need to succeed? Bachelor’s degree in computer science, Software Engineering, Data Science, or a related field, or equivalent practical experience. 7+ years of qualified software engineering experience, including 5+ years building and operating solutions on AWS.

Hands-on experience delivering AI, Machine Learning, or Generative AI solutions in production environments.

Strong Python development skills and experience designing, testing, and integrating RESTful APIs and event-driven services.

Practical experience with Amazon Bedrock and core AWS application services such as AWS Lambda, Amazon API Gateway, AWS Step Functions, Amazon Event

Bridge, Amazon S3, Amazon DynamoDB, and Amazon Aurora or Amazon RDS.

Experience building RAG solutions, including document ingestion, chunking, embeddings, retrieval, grounding, evaluation, and vector databases or vector-search services.

Experience developing AI agents or tool-using workflows, including orchestration, state or memory, safe tool access, error handling, and human approval points.

Working knowledge of AWS security and operations, including AWS IAM, AWS KMS, secrets management,



logging, monitoring, tracing, and incident support.

Experience with Git-based development, automated testing, CI/CD, and infrastructure as code using Terraform, AWS CDK, or AWS Cloud

Formation.

Understanding of containerization and cloud deployment patterns using Docker and at least one of Amazon ECS or Amazon EKS.

Strong communication, collaboration, analytical, and problem-solving skills, with the ability to explain technical decisions to varied stakeholder groups.

Preferred qualifications Experience with Amazon Bedrock Knowledge Bases, Amazon Bedrock Guardrails, Agents for Amazon Bedrock, or Amazon Bedrock Agent

Core.

Experience with Amazon Sage

Maker for custom machine learning development, training, deployment, or MLOps.

Experience with Amazon Open

Search Service, PostgreSQL with pgvector, or other enterprise vector-search technologies.

Experience with AWS Glue, data pipelines, PySpark, or analytics workloads.

Experience developing user interfaces with React. A relevant AWS certification.

Experience with Amazon Quick

Sight when analytics dashboard development is part of the solution.

What’s in it for you We’re honoured to be recognized as a 2026 Best Workplaces in Canada by Great Place to Work® Canada.

Wellness programs that support the three pillars of your health – mental, physical, and financial The prospect to move along a variety of career paths with amazing networking potential.

As a hybrid organization, you and your leader use business and Client needs to choose where you work, at home or in the office Unique Requirements: This role requires Reliability Status Clearance.

In addition to a law enforcement inquiry and a credit check, as part of your application, the Government of Canada will ask if you lived or travelled outside of Canada for 6-consecutive months during the last 5 years, and you must account for all activities during this time.

Important: Obtaining Reliability Status Clearance within a reasonable amount of time is a condition required to start employment for this role at Sun Life.

Must be able to satisfactorily complete applicable background checks prior to the start date and during employment, in accordance with Sun Life’s policies and practices.

📌 Lead AI Engineer (Toronto)
🏢 Sun Life
📍 Toronto