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:

The AI Developer is responsible for building, integrating, and optimizing AI and machine‑learning 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 cloud‑based 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 as Docker, Kubernetes
   

Qualifications

• Bachelor’s 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 well‑documented 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 (stand‑ups, sprint planning, retrospectives).

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

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