Senior ai platform engineer with python/java experience to help build a agentic ai platform with one of our major insurance clients- 16388

Senior AI Platform Engineer with Python/Java experience to help build a agentic AI platform with one of our major insurance clients- 16388

Estimated Start Date: 04/01/2026-- 12/31/2026 and potential for extension

Location: Toronto/Hybrid- 3 days a week on site

Hours: 37.5 Hours Per Week

Job Description

Senior AI Platform Engineer

We are building an Agentic AI Platform within the company that powers next generation intelligence across the enterprise-autonomous task execution, reasoning based workflows, tool calling, retrieval augmented capabilities, multi agent ecosystems, and safety governed automation.

As a Senior AI Platform Engineer, you will help design, build and deliver the foundational services that enable secure, scalable, and reusable AI and multi-agentic workflow solutions across the organization to plan, reason, act, collaborate, and integrate deeply with business systems. You will work across cloud, distributed systems, orchestration frameworks, vector/memory stores, agent workflows, and safety/guardrail layers to ensure the platform is secure, scalable, and enterprise ready. This role is ideal for engineers who blend strong systems engineering skills with curiosity for cutting edge AI patterns.

Position Responsibilities:

Agentic AI Platform Engineering & Core Services

• Build and operate AI platform services and abstractions that support diverse AI use cases, with automation-first delivery.
• Develop reusable reference patterns, inner-source components that meet reliability, security, and compliance standards.
• Implement shared runtimes for multi agent coordination, state management, memory persistence, and messaging.
• Design interoperable APIs/SDKs used by data scientists and developers to build agent powered applications.
• Maintain and improve CI/CD pipelines and developer toolchains for AI services to enable rapid, compliant delivery.
• Evaluate emerging AI/ML infrastructure capabilities; prototype and introduce tools that improve developer productivity and reliability.

Cloud, Infrastructure & Distributed Systems

• Develop and operate scalable backend services supporting high traffic agent interactions, retrieval operations, and real time execution flows.
• Use cloud native technologies (containers, orchestration, IaC, CI/CD) to deliver reliable, cost-efficient services.
• Optimize runtime performance across CPU/GPU/accelerator workloads.

Retrieval, Memory & Knowledge Integration

• Develop standardized retrieval frameworks (search, embeddings, knowledge connectors) enabling agents to access enterprise knowledge safely.
• Build and optimize short term memory, long term memory, and episodic state abstractions for agent workflows.
• Integrate structured/unstructured data sources through unified connectors and retrieval bridges.

Tooling, Connectors & Ecosystem Enablement

• Build tool interfaces that allow agents to invoke enterprise systems, APIs, databases, and automations.
• Create reusable patterns for function/tool definitions, schema validation, safe execution, rate limiting, and auditability.
• Work with North America and other regional business teams to onboard Asia specific systems and workflows into the global agent ecosystem.

Agent Safety, Governance & Observability

• Build and support AI Governance platform and service requirements.
• Build observability for agent workflows: traces, reasoning logs, action sequences, feedback loops, and performance metrics.
• Provide mechanisms for feedback, oversight, and ongoing evaluation of agent behavior.

Developer Experience & Collaboration

• Build templates, scaffolding, and CLI tools to enable quick development of agent powered applications.
• Partner with global engineering, security, and AI governance teams to localize the platform for cross-geo and Asia’s regulatory and data residency needs.
• Mentor engineering and data science teams on agentic design patterns and platform capabilities.
• Evaluate emerging AI/ML infrastructure capabilities; prototype and introduce tools that improve developer productivity and reliability.
• Contribute to documentation, playbooks, and enablement for engineering and data science communities.

Required Qualifications:

• Above 5 years' experience in backend/platform/cloud systems engineering (Jenkins, github, Terraform )
• Proficiency with Python and Java/Scala/TypeScript or similar languages for building backend services and automation.
• Understanding of LLM systems, retrieval architectures, embeddings, vector stores, and prompt/tool orchestration fundamentals.
• Hands on experience with cloud-native development: Azure Kubernetes, containers, CI/CD.
• Strong grasp of API design, asynchronous workflows, concurrency, and system reliability.
• Familiarity with security, governance, and compliance concepts related to AI or data systems.

Ability to collaborate across global teams and translate business problems into platform capabilities.

Story Behind the Need - Business Group & Key Projects:

Can you please provide an overview of what a typical day in this role would look like, including any team members they’d be working with, structure, size, and day-to-day duties We are currently looking to bring in Platform Engineers and Operations Engineers to support a global AI platform within Manulife. This is a newly forming team, and these roles represent the first set of headcounts we are looking to establish.

The focus will be on:

• Platform Engineering capabilities to help design, build, and scale the AI platform
• Operations Engineering expertise with strong automation experience to support reliability, scalability, and operational excellence

Given that the team is being built from the ground up, we’re looking for candidates who are comfortable working in an evolving environment and can help shape foundational processes, tooling, and standards.

Disclaimer

AI may be used in evaluating candidates.

This posting is for an existing vacancy. Apply