Associate AI Engineer

The Associate AI Engineer will join the AI team supporting the Long-Term Care program in John Hancock and Manulife. This role will contribute to building deploying and maintaining AI solutions that improve business processes risk insights and customer experience across the Long-Term Care value chain.

The ideal candidate is a quick learner eager to build hands-on experience in machine learning Generative AI and production AI systems and interested in staying current with emerging trends in AI engineering and cloud technologies. You will work closely with senior engineers data scientists and business partners to turn ideas and prototypes into production-ready AI solutions.

Position Responsibilities:

• Support the design development and deployment of AI and ML solutions for the Long-Term Care program.
• Work with Data Scientists and AI Engineers to help build and maintain ML and GenAI pipelines (data preparation feature engineering model training and evaluation).
• Assist in deploying models into production environments using modern engineering practices.
• Help monitor model performance including accuracy drift and reliability and support troubleshooting and improvements.
• Contribute to both traditional ML use cases (predictive models classification forecasting) and GenAI use cases (summarization document processing RAG automation).
• Develop and maintain APIs and services that integrate AI solutions into business workflows.
• Follow established MLOps and LLMOps practices including version control testing and documentation.
• Support building observability tools such as logging dashboards and alerts.
• Collaborate with cross-functional teams including engineering data business and governance teams.
• Ensure solutions follow enterprise standards for security compliance and responsible AI.
• Continuously learn and apply new tools frameworks and best practices in AI ML and software engineering.

Required Qualifications:

• Bachelors degree in Computer Science Data Science Engineering Mathematics Statistics or a related field.
• Strong programming skills in Python.
• Foundational understanding of machine learning concepts (supervised/unsupervised learning model evaluation feature engineering).
• Basic experience with ML or AI projects either through coursework internships or personal projects.

Preferred Qualifications:

• Exposure to GenAI or LLMs (e.g. prompt engineering APIs embeddings or RAG concepts).
• Basic understanding of cloud platforms (preferably Azure) and modern development tools.
• Familiarity with version control (Git) and basic software engineering practices.
• Basic knowledge of data processing using SQL or data tools.
• Strong problem-solving skills and willingness to learn.
• Good communication skills and ability to work in a team environment.

When you join our team:

• Well empower you to learn and grow the career you want.

• Well recognize and support you in a flexible environment where well-being and inclusion are more than just words.

• As part of our global team well support you in shaping the future you want to see.

#LI-Hybrid

The role being advertised is an existing vacancy.

About Manulife and John Hancock

Manulife Financial Corporation is a leading international financial services provider helping people make their decisions easier and lives better. To learn more about us visit is an Equal Opportunity Employer

At Manulife/John Hancock we embrace our diversity. We strive to attract develop and retain a workforce that is as diverse as the customers we serve and to foster an inclusive work environment that embraces the strength of cultures and individuals. We are committed to fair recruitment retention advancement and compensation and we administer all of our practices and programs without discrimination on the basis of race ancestry place of origin colour ethnic origin citizenship religion or religious beliefs creed sex (including pregnancy and pregnancy-related conditions) sexual orientation genetic characteristics veteran status gender identity gender expression age marital status family status disability or any other ground protected by applicable law.

It is our priority to remove barriers to provide equal access to employment. A Human Resources representative will work with applicants who request a reasonable accommodation during the application process. All information shared during the accommodation request process will be stored and used in a manner that is consistent with applicable laws and Manulife/John Hancock policies. To request a reasonable accommodation in the application process contact .

Referenced Salary Location

Salary range is expected to be between

Employees also have the opportunity to participate in incentive programs and earn incentive compensation tied to business and individual performance. The actual salary will vary depending on local market conditions geography and relevant job-related factors such as knowledge skills qualifications experience and education/training. If you are applying for this role outside of the primary location please contact for the salary range for your location.

Manulife/John Hancock offers eligible employees a wide array of customizable benefits including health dental mental health vision short- and long-term disability life and AD&D insurance coverage adoption/surrogacy and wellness benefits and employee/family assistance plans. We also offer eligible employees various retirement savings plans (including pension/401(k) savings plans and a global share ownership plan with employer matching contributions) and financial education and counseling resources. Our generous paid time off program in the U.S. includes up to 11 paid holidays 3 personal days 150 hours of vacation and 40 hours of sick time (or more where required by law) each year and we offer the full range of statutory leaves of absence.

We use data and analytics technologies such as artificial intelligence (AI) and automated processing tools to analyze and process the information you provide to us or third parties in the application process. For more information please refer to our personal information collection statement.

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