Opens LinkedIn
- Employment type
- Contract
- Experience level
- Senior · 5+ years
- Minimum education
- Bachelor’s degree
- Posting language
- English
- Working hours
- 40 hours per week
- Seniority
- Mid-Senior level
Job summary
Design, build, and operate enterprise AI platform infrastructure and gateways, and develop and deploy AI, Generative AI, and agentic solutions and workflows. Implement CI/CD, Infrastructure-as-Code, and MLOps/LLMOps practices while supporting AI governance, observability, monitoring, responsible AI controls, and team standards.
Job details
Our Toronto Financial Client is seeking two AI Platform Engineers to support a large enterprise AI transformation program. The successful candidates will design, build, and operate AI platform infrastructure that enables enterprise AI, Generative AI, and Agentic AI solutions at scale. Responsibilities Design and manage enterprise AI platform infrastructure and AI gateways. Build and operationalize AI, GenAI, and Agentic AI solutions. Develop and deploy AI agents and agentic workflows. Implement CI/CD pipelines, Infrastructure-as-Code, and MLOps/LLMOps best practices. Support AI governance, observability, monitoring, and responsible AI controls. Mentor team members and contribute to AI delivery standards and best practices. Required Qualifications Degree in Computer Science, Engineering, or a related field. 5–8+ years of platform engineering, infrastructure, or DevOps experience supporting AI workloads. Strong Python development skills. Experience with Infrastructure-as-Code (Terraform). Hands-on experience with Docker and Kubernetes. Experience with major cloud AI ecosystems and open-source AI platforms. Knowledge of AI monitoring and observability tools. Experience building and deploying AI agents using frameworks such as LangGraph, CrewAI, or cloud-based agentic AI platforms. Strong API integration and development experience. Consulting or professional services experience preferred. Technical Environment Python Terraform Docker Kubernetes MLOps / LLMOps AI Gateways LangGraph CrewAI Agentic AI Generative AI Cloud AI Platforms CI/CD API Development ,
What you’ll do
Design, build, and operate enterprise AI platform infrastructure and gateways, and develop and deploy AI, Generative AI, and agentic solutions and workflows. Implement CI/CD, Infrastructure-as-Code, and MLOps/LLMOps practices while supporting AI governance, observability, monitoring, responsible AI controls, and team standards.
Requirements
Requires a degree in Computer Science, Engineering, or a related field, along with 5–8+ years of platform engineering, infrastructure, or DevOps experience supporting AI workloads. Candidates need strong Python, Terraform, Docker, Kubernetes, cloud AI platform, AI observability, agent framework, and API development experience; consulting or professional services experience is preferred.
Listed skills
- Kubernetes · Preferred
- CI/CD · Preferred
- Docker · Preferred
- Terraform · Preferred
- Python · Preferred
Other relevant skills
Identified from the job description. Confirm important requirements above.
- Python
- Terraform
- Docker
- Kubernetes
- Platform Engineering
- Infrastructure-As-Code
- MLOps
- LLMOps
- AI Gateways
- Generative AI
- Agentic AI
- AI Agents
- LangGraph
- CrewAI
- CI/CD
- API Development
Job areas
- Technology
- Software
- Engineering
- Data & Analytics
- Finance & Accounting
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