Lead AI Engineer

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

Job summary

Sun Life Corporate IT is seeking a Lead AI Engineer to design, develop, deploy, and support enterprise-grade AI/ML solutions on AWS. You will drive RAG-enabled applications, intelligent agents, and automation workflows, collaborating with architects, data engineers and business stakeholders to deliver secure, scalable AI platforms.

The successful candidate brings 7+ years of software engineering experience, 5+ years on AWS, deep Python skills, and hands-on Bedrock experience to production

Qualifications

• Bachelor's degree in computer science, Software Engineering, Data Science, or 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, API Gateway, Step Functions, EventBridge, S3, DynamoDB, and Aurora/RDS.
• Experience building RAG solutions, including document ingestion, chunking, embeddings, retrieval, grounding, evaluation.

Responsibilities

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

Skills

Python development

AI/ML

RESTful APIs

Agile

Mentoring

Education

Bachelor's degree in Computer Science or related field

Tools

Amazon Bedrock

AWS Lambda

API Gateway

Step Functions

EventBridge

S3

DynamoDB

Aurora/RDS

ECS/EKS

KMS / IAM

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:

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 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, an