AI Engineer - Hybrid

Manulife Financial; Boston (MA); Hybrid; USD 90,000 - 167,000; Full time

Job summary

Manulife Financial invites applications for an AI Engineer to join the Long-Term Care AI team. You will design, build, deploy, and scale production-grade AI solutions across John Hancock and Manulife, driving improved outcomes and customer experiences.

The ideal candidate has hands-on experience delivering AI models to production, strong MLOps capabilities, and proficiency with modern cloud-native tooling (Azure, Databricks, MLflow, Docker, Kubernetes). Hybrid work is supported.

Qualifications

• 3+ years of experience in AI/ML engineering or related field.
• Strong Python programming and production-grade code development.
• Experience deploying ML/AI models into production cloud environments.
• Hands-on experience with MLOps, including versioning, registry, CI/CD, testing, monitoring, retraining workflows.
• Experience monitoring model performance in production (accuracy, drift, latency, reliability).
• Strong understanding of traditional ML, predictive analytics, feature engineering, evaluation and experimentation.
• Experience with GenAI/LLM-based solutions, including prompt engineering and embeddings.
• Experience with cloud platforms (preferably Azure) and tools like Azure ML, Azure OpenAI, Databricks, MLflow, Docker, Kubernetes, GitHub Actions, Azure DevOps.

Responsibilities

• Design, build, and deploy production-ready AI/ML solutions for Long-Term Care program.
• Partner with cross-functional teams to translate business needs into scalable AI products.
• Build and maintain modular ML/GenAI pipelines (data processing, feature engineering, training, evaluation, deployment, monitoring).
• Operationalize ML models and predictive analytics (classification, regression, forecasting, risk scoring).
• Implement GenAI/LLM-based solutions (RAG, embeddings, document intelligence, automation).
• Deploy models into production using containerization, CI/CD, testing, version control, cloud-native infra.
• Monitor production models for performance, drift, latency, cost, reliability.
• Build observability (logs, metrics, dashboards, alerts) and ensure governance and security alignment.

Skills

Python

Production AI

MLOps & LLMOps

Cloud-native dev

GenAI & LLMs

Model monitoring

CI/CD

Collaboration

Tools

Azure ML

Azure OpenAI

Databricks

MLflow

Docker

Kubernetes

GitHub Actions

Azure DevOps

Job description

AI Engineer

Job Posting Description

The AI Engineer will join the AI team supporting the Long-Term Care program in Manulife/John Hancock. This role will help design, build, deploy, and scale production-grade AI solutions that improve business outcomes, operational efficiency, risk management, and customer experience across the Long-Term Care value chain.

The ideal candidate is passionate about AI and technology, a lifelong learner, and someone who actively follows the latest trends in AI Engineering, ML Engineering, Generative AI, LLMs, cloud-native development, and modern software engineering. This individual should bring strong hands‑on experience in deploying models to production, monitoring model performance, and applying established MLOps and LLMOps frameworks.

This role requires a strong blend of AI, traditional data science, predictive analytics, machine learning, GenAI, and production engineering. The successful candidate will work closely with Data Scientists, Data Engineers, Product Owners, Business Partners, and Technology teams to turn prototypes into reliable, scalable, and well‑governed AI products.

Position Responsibilities

• Design, build, and deploy production‑ready AI and ML solutions that support the Long‑Term Care program across John Hancock and Manulife.
• Partner with Data Scientists, Data Engineers, Business Analysts, and Product teams to translate business needs into scalable AI products.
• Build and maintain modular, reusable ML and GenAI pipelines, including data processing, feature engineering, model training, evaluation, deployment, and monitoring.
• Operationalize traditional ML models and predictive analytics solutions, including classification, regression, forecasting, risk scoring, segmentation, and anomaly detection.
• Implement GenAI and LLM‑based solutions, including retrieval‑augmented generation, prompt orchestration, document intelligence, summarization, classification, and intelligent workflow automation.
• Deploy models and AI services into production using modern engineering practices such as containerization, CI/CD, automated testing, version control, and cloud‑native infrastructure.
• Monitor production models for performance, data drift, model drift, bias, accuracy degradation, latency, cost, and reliability using established MLOps and LLMOps practices.
• Build observability capabilities, including logging, tracing, metrics, alerts, dashboards, and service‑level monitoring.
• Collaborate with Risk, Legal, Compliance, Security, Architecture, and Cloud teams to ensure AI solutions are secure, compliant, explainable, and aligned with enterprise standards.
• Support model governance activities, including documentation, validation, auditability, model lineage, and responsible AI controls.
• Evaluate and adopt fit‑for‑purpose tools, frameworks, and platforms across Azure, Databricks, Azure OpenAI, MLflow, vector databases, and internal AI platforms.
• Engineer AI services that integrate with business workflows through APIs, event‑driven architecture, batch pipelines, and enterprise applications.
• Continuously improve solution quality, scalability, maintainability, and cost efficiency.
• Stay current with emerging trends in AI, ML, GenAI, LLMOps, software engineering, cloud platforms, and financial services technology, and share relevant learnings with the team.
• Mentor junior engineers and data scientists on production engineering standards, clean code, testing, monitoring, and MLOps/LLMOps best practices.

Required Qualifications

• 3+ years of experience in AI Engineering, ML Engineering, Software Engineering, Data Science Engineering, or a related technical role.
• Strong programming skills in Python, with experience building reliable, maintainable, and production‑quality code.
• Proven experience deploying ML or AI models into production cloud environments.
• Hands‑on experience with MLOps practices, including model versioning, model registry, CI/CD, automated testing, monitoring, retraining workflows, and production support.
• Experience monitoring model performance in production, including accuracy, drift, latency, stability, reliability, and business performance indicators.
• Strong understanding of traditional machine learning and predictive analytics techniques, including supervised learning, unsupervised learning, feature engineering, model evaluation, and experimentation.
• Practical experience with GenAI and LLM‑based solutions, including prompt engineering, RAG, embeddings, vector search, evaluation, and guardrails.
• Experience working with cloud platforms, preferably Azure, and tools such as Azure ML, Azure OpenAI, Databricks, MLflow, Docker, Kubernetes/AKS, GitHub Actions, or Azure DevOps.
• Strong SQL skills and experience working with structured and unstructured data.
• Experience with data engineering concepts, including ETL/ELT, Spark, Databricks, Delta Lake, data quality, and scalable data pipelines.
• Strong understanding of software engineering best practices, including API design, unit testing, integration testing, code reviews, documentation, and secure development.
• Ability to work with cross‑functional teams and communicate technical concepts clearly to both technical and non‑technical stakeholders.
• Demonstrated ability to balance speed, quality, risk, and long‑term maintainability.

Preferred Qualifications

• Bachelor’s degree in Computer Science, Software Engineering, Data Science, Mathematics, Statistics, Engineering, or a related technical field, or equivalent industry experience.
• Master’s or PhD degree in a relevant discipline is an asset.
• Experience in insurance, financial services, healthcare, Long‑Term Care, claims, underwriting, risk management, or operations is an asset.
• Experience with model governance, responsible AI, explainability, fairness testing, or regulated AI environments.
• Experience with document intelligence, claims analytics, call center analytics, workflow automation, or knowledge management solutions.
• Experience with vector databases or search technologies such as Azure AI Search, Elastic, Pinecone, FAISS, or similar tools.
• Experience building production‑grade GenAI applications using orchestration frameworks, agentic patterns, evaluation frameworks, and guardrails.

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 https://www.manulife.com/en/about/our-story.html

Manulife 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 [e-mail].

Referenced Salary Location

Boston, Massachusetts

Working Arrangement

Hybrid

Salary range is expected to be between

$90,160.00 USD - $167,440.00 USD

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 [e-mail] 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.

Know Your Rights I Family & Medical Leave I Employee Polygraph Protection I Right to Work I E-Verify

Company: John Hancock Life Insurance Company (U.S.A.)