Manager, Enterprise AI Services Engineering
Thomson Reuters View all jobs
- Toronto, ON
- Permanent
- Full-time
TR AI Gateway service - TR's central gateway through which product teams access large language models across Azure, AWS, and GCP.
The successful candidate will lead a globally distributed team of full-time engineers and contractors across AMERS and APAC regions, drive quarterly engineering delivery against ADO sprint plans, and partner closely with Service Architecture, Enablement, Product Management, and Platform Engineering leadership to keep EAIS secure, scalable, and
strategically aligned with TR's AI ambitions.About the RoleAs a Manager, Enterprise AI Services Engineering, you will:
- Lead and manage a globally distributed team of full-time engineers and contractors
- Own the quarterly engineering planning cycle using Azure DevOps Boards, running bi-weekly SCRUM ceremonies and maintaining sprint velocity and team health
- Drive deployment, implementation, and engineering of AI systems, tools, and pipelines across Azure, AWS, and GCP environments
- Ensure reliable, production-grade operations of the TR AI Gateway Service and other AI services with a strong focus on SLOs and incident management
- Maintain and improve CI/CD automation pipelines and infrastructure-as-code practices (cloud-iac) across multi-cloud environments
- Serve as the engineering bridge between EAIS Architecture (design and roadmap) and Service Engineering (build and operate), translating architectural decisions into executable delivery plans
- Partner with the Enablement team to support customer onboarding, intake management, and LLM consumer success across TR product teams
- Contribute to Core Platform Services OKR planning and quarterly reviews, owning EAIS engineering objectives
- Represent the team in Platform Engineering leadership forums, providing delivery, risk, and roadmap visibility to Core Platform Services and Platform Engineering leadership
- Ensure compliance with TR's AI Security Guidelines, FedRAMP requirements, and enterprise identity and access management standards (SailPoint, PingID, CyberArk, Venafi)
- Drive security hygiene through Snyk AppSec, certificate management, and GitHub signed-commit practices
- Manage Datadog observability across production and non-production environments, ensuring dashboards, alerting, and incident response are production-ready
- Support career development and performance management for direct reports
- Manage contractor relationships and hold vendors accountable to delivery standard
- 7+ years of software or cloud engineering experience, with 3+ years in an engineering management or technical lead role
- Deep hands-on experience with multi-cloud platforms: Azure (required), AWS (required), GCP (preferred
- Proven experience managing enterprise AI, ML, or LLM platform engineering teams in production environments
- Strong foundation in DevOps and CI/CD practices, including infrastructure-as-code,
- GitOps, and container orchestration (Kubernetes)
- Experience with agile delivery frameworks (Scrum/Kanban) using Azure DevOps Boards or equivalent tooling
- Familiarity with observability platforms (Datadog) and enterprise ITSM tools (ServiceNow)
- Understanding of enterprise identity and access management, cloud security, and compliance requirements
- Demonstrated ability to manage globally distributed, blended teams across time zones and cultures
- Collaborative approach to working across Architecture, Enablement, Product, and Cloud Engineering teams
- Experience with LLM orchestration layers, retrieval-augmented generation (RAG) pipelines, or enterprise GenAI platforms
- Familiarity with FedRAMP compliance requirements and regulated cloud environments
- Experience with Vertex AI, Azure OpenAI, or AWS Bedrock integration
- Prior experience in a Platform Engineering, CIO Technology, or shared services organization
- Vendor and contractor management experience across global delivery models