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Added 2 mins ago
Enterprise Account Executive
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Sun Life

Lead AI Engineer

Toronto, ON, Canada
Waterloo, ON, Canada
Sun Life Toronto Atria, Canada

Job type: Full-time
Apply by: Sep 30, 2026
Experience: 7+ years of professional software engineering experience, including 5+ years building and operating solutions on AWS.
Posting language: English
Posted: Sep 22, 2026

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Original job description

You are as unique as your background, experience and point of view. Here, you’ll be encouraged, empowered and challenged to be your best self. You'll work with dynamic colleagues - experts in their fields - who are eager to share their knowledge with you. Your leaders will inspire and help you reach your potential and soar to new heights. Every day, you'll have new and exciting opportunities to make life brighter for our Clients - who are at the heart of everything we do.

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.

When you join Sun Life, you'll work with passionate colleagues and empowering leaders who support your growth and celebrate your contributions, so you can make a meaningful difference in our Clients' lives.

Discover how you can make a difference in the lives of individuals, families and communities around the world.

Job Description:

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 EventBridge, 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 professional 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 EventBridge, 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 CloudFormation.
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 AgentCore.
Experience with Amazon SageMaker for custom machine learning development, training, deployment, or MLOps.
Experience with Amazon OpenSearch 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 QuickSight 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.
We are thrilled to be recognized by Excellence Canada with their top-level certification, the Canada Order of Excellence for Mental Health at Work®, for prioritizing employee well-being, fostering a positive work culture, and achieving excellence in mental health.
Wellness programs that support the three pillars of your health – mental, physical, and financial
The opportunity 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.

The Base Pay range is for the primary location for which the job is posted. It may vary depending on the work location of the successful candidate or other factors. In addition to Base Pay, eligible Sun Life employees participate in various incentive plans, payment under which is discretionary and subject to individual and company performance. Certain sales focused roles have sales incentive plans based on individual or group sales results.

Diversity and inclusion have always been at the core of our values at Sun Life. A diverse workforce with wide perspectives and creative ideas benefits our Clients, the communities where we operate and all of us as colleagues. We welcome applications from qualified individuals from all backgrounds.

Persons with disabilities who need accommodation in the application process, or those needing job postings in an alternative format, may e-mail a request to [email protected].

We are proud to be a hybrid organization that offers our employees the choice and flexibility to work from both the office and virtually based on the needs of the business, our Clients and you.

We may use artificial intelligence to support candidate sourcing, screening, interview scheduling.

We thank all applicants for showing an interest in this position. Only those selected for an interview will be contacted.

Salary Range:

90,000/90 000 - 140,000/140 000

Job Category:

IT - Application Development

Posting End Date:

29/09/2026

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More about this job

Responsibilities

Design, develop, and deploy enterprise-grade AI, Machine Learning, and Generative AI solutions on AWS. Collaborate with cross-functional teams to build scalable, secure, and production-ready AI-powered applications and automation workflows.

Requirements

Requires a bachelor's degree in a relevant field and over 7 years of professional software engineering experience, including 5+ years on AWS. Candidates must have hands-on experience with production AI/ML solutions, Python, and AWS services like Amazon Bedrock.

Skills

Artificial Intelligence
Machine Learning
Generative AI
AWS
Python
Amazon Bedrock
RAG
Prompt Engineering
Intelligent Agents
Software Engineering
Cloud Computing
CI/CD
Infrastructure as Code
Terraform
API Development
Data Engineering

Benefits

Wellness programs
Mental health support
Financial health support
Career development opportunities
Networking potential

Visa sponsorship

Not detected in the job text

Keywords

Artificial Intelligence
Machine Learning
Generative AI
AWS
Amazon Bedrock
Python
RAG
Cloud Architecture
Serverless
Containerization
Docker
Kubernetes
Terraform
CI/CD
Infrastructure as Code
RESTful APIs
Data Engineering
Security Governance
Agile
Amazon S3
Amazon DynamoDB
Amazon Aurora
AWS Lambda
Amazon API Gateway
AWS Step Functions
Amazon EventBridge
Prompt Engineering
MLOps
Vector Databases
Reliability Status Clearance

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