Senior Data Platform Engineer

at  Manulife

Manulife Canada is a leading international financial services provider, dedicated to helping people make decisions easier and lives better. We are seeking a highly skilled and motivated AI and Cloud Platform Engineer to join our dynamic technology team. This role offers a unique opportunity to work on innovative projects involving Generative AI (GenAI), Large Language Models (LLM), and Retrieval-Augmented Generation (RAG), with a strong focus on cloud engineering.

General Responsibilities

• Builds and owns the infrastructure and tools required for processing and storing data from a wide variety of data sources, including infrastructure that can handle the scale of ML and AI workloads.
• Designs, develops, and optimizes data pipelines, architectures, and data sets, ensuring efficient data ingestion, transformation, and reliable delivery using modern tools and practices.
• Collaborates within and across teams (e.g., with Data Engineers, Data Scientists), and other customers to understand complex data requirements.
• Assists data users in defining requirements and refining existing processes using a wide variety of tools.
• Integrates new tools and solutions that can empower the organization’s data consumers and help assimilate them.
• Implements data monitoring and alerting solutions to proactively identify and address data issues.
• Implements systems to monitor the performance of deployed AI models.

General Technical and Functional Knowledge:

• 6+ years Data Platform Engineer experience
• Experience maintaining and extending Infrastructure as Code (IaC) modules for the data platform using leading practices.
• Ability to develop IaC scripts and modules to provision new cloud infrastructure.
• Ability to integrate IaC scripts with DevOps and Build pipelines.
• Ability to implement CI/CD pipelines for IaC deployments.
• Experience configuring RBAC and access controls via automation or CLI for cloud services.
• Experience participating in requirements, design, and solution discussions for application, architecture, networking, and infrastructure.

AI Engineering:

• Design, develop, and implement AI solutions using GenAI, LLMs, and RAG methodologies.
• Engineer prompts for AI models to improve their accuracy and utility in various applications.
• Conduct comprehensive testing and validation of AI models to ensure robust and accurate outputs.
• Collaborate with data scientists, software developers, and other customers to integrate AI models into existing systems.
• Maintain and optimize existing AI systems to improve their performance and reliability.
• Stay updated with the latest advancements in AI and related technologies to continually enhance Manulife’s AI capabilities.

Cloud Platform Management:

• Initialize and manage cloud platforms with Azure.
• Develop, maintain, and test data pipelines, application frameworks, and infrastructure for data generation.
• Employ Azure Functions to deploy scalable cloud-based solutions.
• Implement event-based architecture to facilitate real-time data processing and integration.

Software Development:

• Build, code, test, and maintain high-quality software.
• Translate user requirements into software requirements.
• Develop and maintain applications using Python, ensuring high-quality code and performance.
• Use the Microsoft Power Platform to create custom business applications and workflows.
• Participate in Agile sprints and ceremonies to support rapid iteration and development.

Collaboration and Contribution:

• Work closely with information architects and data scientists.
• Participate in functional demos using new technologies.
• Collaborate with team members, participate in code reviews, and share skills and methods.

Continuous Learning:

• Stay abreast of developments in your technical subject area and recognize and translate these to your working environment.
• Experiment with emerging technologies and understand how they will impact future developments.

• Builds and owns the infrastructure and tools required for processing and storing data from a wide variety of data sources, including infrastructure that can handle the scale of ML and AI workloads.
• Designs, develops, and optimizes data pipelines, architectures, and data sets, ensuring efficient data ingestion, transformation, and reliable delivery using modern tools and practices.
• Collaborates within and across teams (e.g., with Data Engineers, Data Scientists), and other customers to understand complex data requirements.
• Assists data users in defining requirements and refining existing processes using a wide variety of tools.
• Integrates new tools and solutions that can empower the organization’s data consumers and help assimilate them.
• Implements data monitoring and alerting solutions to proactively identify and address data issues.
• Implements systems to monitor the performance of deployed AI models