Who you are

- Approximately 7+ years of professional software engineering experience designing, building, and operating large-scale backend systems in production environments in a lead capacity for 1-2 years

- Solid proficiency in Python (FastAPI or similar) or another backend language, with experience building distributed systems, microservices, and cloud-native applications

- Hands-on expertise with relational databases (e.g. PostgreSQL) and caching/messaging technologies (e.g. Redis), API design, AWS services including cloud AI runtimes (e.g. AWS Bedrock AgentCore), and container orchestration with Kubernetes (EKS)

- Experience building and operating CI/CD pipelines, Infrastructure-as-Code solutions, and progressive delivery or release-engineering practices

- Strong experience with observability, monitoring, and troubleshooting production systems using technologies such as OpenTelemetry, Datadog, Prometheus, or similar tools

- Experience supporting or integrating with AI/LLM-powered systems, including agent runtimes, LLM gateways, RAG architectures, retrieval systems, or related AI infrastructure

- Proven strength in system design, debugging, performance optimization, and making thoughtful trade-offs between short-term delivery and long-term scalability

- Demonstrated ability to influence technical decisions, collaborate across engineering and product teams, and communicate effectively with both technical and non-technical stakeholders

What the job involves

- As a Lead Platform Engineer, you'll provide technical leadership for critical platform capabilities, helping shape the architecture, reliability, and evolution of systems that support AI agent workflows across the business





- You'll partner closely with Product, Applied AI, and Engineering teams to accelerate the delivery of AI-driven innovation while maintaining high standards for scalability, performance, and operational excellence

- Lead the design, architecture, and delivery of backend and platform services that power AI agent workflows, ensuring scalable, reliable, and maintainable solutions across a microservices and event-driven ecosystem

- Own and evolve cloud infrastructure, CI/CD systems, and progressive delivery capabilities using Infrastructure-as-Code practices, enabling safe, continuous deployment and efficient developer workflows

- Drive cross-functional technical initiatives with Product, Applied AI, and Infrastructure teams, aligning priorities and leading complex projects from design through production

- Improve platform reliability, observability, performance, and cost efficiency through monitoring, incident response, root-cause analysis, and operational excellence across Kubernetes and managed AI runtimes

- Improve system performance, resilience, and cost efficiency by strengthening monitoring, incident response, and root-cause analysis for production systems running on managed cloud AI runtimes (e.g. AWS Bedrock AgentCore) and Kubernetes

- Mentor engineers, influence technical direction, and help raise the bar for code quality, testing, reliability, and engineering best practices across the organization

- Participate in an on-call rotation supporting customer-facing systems and internal platform tooling, contributing to a culture of ownership and continuous improvement

The application process

- End Date: December 30, 2026

📌 Lead Platform Engineer (Toronto)
🏢 Thomson Reuters
📍 Toronto