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Job Description & How to Apply Below
Role: AI Platform Engineer
Start date: ASAP
End date:
October 31st, 2027
Number of resources needed: 2
Location & work model:
Toronto, ON - Hybrid (2-3 times per week onsite)
Project Background:
- You will work across complex client engagements building and operationalising AI platform infrastructure that underpins enterprise agentic AI solutions. Partnering with AI Architects and AI Engineers, you will own the MLOps and LLMOps discipline, from CI/CD pipelines and model registries to telemetry, evaluation guardrails, and responsible AI controls.
- As an AI Platform Engineer, you will design, build, and operate the foundational infrastructure layer that powers EY's AI, GenAI and Agentic AI solutions in production. You will own the platform that AI Engineers build on, including AI gateways, agent deployment pipelines, and the observability stack that keeps AI solutions performant, secure, and cost-efficient at enterprise scale. Beyond platform operations, you bring hands-on capability to build and deploy AI agents.
Key Responsibilities:
- Design and manage enterprise AI platform infrastructure, including multi-agent systems, orchestration frameworks, AI Gateways, telemetry, monitoring, guardrail, and agent runtime environments.
- Deploy and operationalise Generative/Agentic AI solutions behind scalable, high-availability architecture, including platform-level support for agentic protocols (e.g. MCP server operations, A2A, LLM proxies), enabling AI Engineers to develop and deploy agent-based solutions.
- Build and deploy AI agents and agentic workflows using AI agent frameworks.
- Implement CI/CD automation, reusable IaC to standardize deployment, best practices for MLOps and LLMOps across experimental and production environments.
- Build AI governance, risk management, and responsible AI controls for autonomous and semi-autonomous systems.
- Contribute to EY thought leadership, assets, and go-to-market offerings in agentic and generative AI.
- Mentor junior team members and contribute to EY AI assets, accelerators and delivery standards
Required Qualifications:
- A degree in Computer Science, Engineering, or a related field.
- 5-8+ years of hands-on background in infrastructure, platform engineering, or Dev Ops, with direct experience supporting AI workloads in production.
- Proficiency in Python and Infrastructure-as-Code tools such as Terraform, with deep experience in containerisation and orchestration platforms (Docker, Kubernetes).
- Working knowledge of major cloud AI ecosystems and open-source platforms
- Working knowledge of agentic AI monitoring and observability suite
- Hands-on experience building and deploying AI agents using open frameworks such as Lang Graph, CrewAI, proprietary cloud-based agentic platforms.
- Deep experience in API integration and development.
- Consulting or professional services experience is strongly preferred
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