GEN AI Engineer

As a GenAI Engineer at Manulife, you will design, build, and maintain advanced data and AI solutions that power our next generation of intelligent applications. You will develop scalable data infrastructure, pipelines, and models that support Generative AI use cases across the organization. This role blends modern data engineering, GenAI innovation, machine learning deployment, and solution design—driving meaningful business outcomes and helping shape the future of AI at Manulife.

• Design, build, and maintain data pipelines to ingest, curate, and index data for AI and Generative AI applications.
• Collaborate with Data Scientists to develop GenAI solutions that solve complex business problems and drive measurable value.
• Build scripts, automation, and analytical tools that accelerate data engineering and model deployment activities.
• Partner with architects and technical leaders to design high-performing GenAI applications aligned with business objectives.
• Deploy machine learning and GenAI models into production environments, ensuring interoperability with systems, APIs, and data sources.
• Participate in solution design sessions, defining technical requirements, deliverables, and timelines.
• Stay current on emerging AI technologies and evaluate their application to improve engineering processes.
• Adopt and promote ML Ops best practices for efficient, reliable model deployment and lifecycle management.
• Contribute to a culture of innovation, collaboration, and continuous learning within the GenAI engineering team.

• Strong understanding of Generative AI concepts, including model architectures, algorithms, and business applications.
• Experience with data indexing, chunking, and optimizing RAG (Retrieval-Augmented Generation) patterns.
• Expertise with CI/CD pipelines and release management for AI or GenAI applications.
• Hands‑on experience working in Azure environments, including Databricks, Data Factory, Storage Accounts, and related services.
• Strong proficiency in Python, PySpark, and SQL.
• Experience using Git for version control and codebase management.
• Knowledge of microservice‑based architectures for GenAI solutions.
• Understanding of database systems, data lakes, No
  
  SQL databases, and large‑scale distributed data solutions.
• Demonstrated experience deploying and supporting large‑scale ML or GenAI models in production.
• Excellent communication skills and the ability to collaborate effectively across cross‑functional teams.
• Highly motivated, adaptable, and results‑oriented, with the ability to thrive in complex, evolving environments.

• Experience optimizing model performance and ensuring scalability to meet enterprise workloads.
• Familiarity with deploying LLMs in cloud environments and setting up monitoring (accuracy, latency, throughput).
• Terraform or Infrastructure‑as‑Code experience for provisioning cloud resources.
• Background in ML Ops, data orchestration, or cloud‑native AI infrastructure.

• We’ll empower you to learn and grow the career you want.
• We’ll recognize and support you in a flexible environment where well‑being and inclusion are more than just words.
• As part of our global team, we’ll support you in shaping the future you want to see.

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