Manager, AI Engineer

You are as unique as your background experience and point of view. Here youll be encouraged empowered and challenged to be your best self. Youll 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 youll have new and exciting opportunities to make life brighter for our Clients - who are at the heart of everything we do.

At Sun Life were 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 youll 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:

The AI Developer is responsible for building integrating and optimizing AI and machinelearning solutions that enhance business applications and workflows. The role focuses on developing AI features using modern frameworks implementing GenAI/RAG components and ensuring solutions are secure scalable and aligned with product requirements.

Key responsibilities

• Develop solutions to support business initiatives automation workflows and GenAI/RAG components using modern AI frameworks.

• Build and integrate APIs data processing pipelines and cloudbased AI services.

• Collaborate with product owners and engineering teams to translate requirements into functional AI solutions.

• Optimize model performance reliability and cost through testing tuning and monitoring.

• Ensure AI solutions follow security quality and deployment standards across environments.
  

Preferred skills

• Hands-on experience in Python and Java

• Familiarity with REST APIs and frameworks such as FastAPI Flask or similar technologies

• Experience with LLM frameworks including LangChain LangGraph and n8n.

• Knowledge of databases such as PostgreSQL and Cosmos DB

• Practical experience with AWS cloud services especially SageMaker and Bedrock

• Strong knowledge of containerization and orchestration tools such asDocker Kubernetes
  

Qualifications

• Bachelors degree in Information Technology Computer Science or related fields.

• Over 6 years of working experience.

• At least 2 years of experience in machine learning or AI with a minimum of 1 year focused on generative AI technologies.

• Proven hands-on experience with Large Language Models (e.g. Claude Nova Pro Qwen) and applications of Generative AI.

• Expertise in prompt engineering with a track record of developing effective strategies.

• Excellent interpersonal and communication skills with the ability to collaborate effectively across teams.
  

Responsibilities

Core Delivery & Execution

• Design develop test and deploy software applications and system components.

• Implement solutions that meet business functional and technical requirements.

• Write clean maintainable and welldocumented code following coding standards.

• Perform code reviews to ensure quality consistency and adherence to best practices.

• Conduct unit integration and regression testing.

• Troubleshoot debug and resolve technical issues across environments.

Quality & Compliance

• Ensure all deliverables meet security performance and reliability standards.

• Maintain compliance with architectural guidelines governance frameworks and technical standards.

• Apply secure coding practices and support vulnerability remediation.

• Supporting auditability and traceability of technical changes through proper version control and documentation.

Collaboration & Communication

• Work closely with product owners architects QA DevOps and business stakeholders.

• Provide technical input during requirement refinement and solution design.

• Participate in agile ceremonies (standups sprint planning retrospectives).

• Contribute to knowledge-sharing via documentation wikis playbooks demos and internal sessions.

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