Lead Platform Engineer

At Thomson Reuters, we're building the platform that powers CoCounsel's AI agent ecosystem. Our Platform Engineering team owns the backend services, cloud infrastructure, deployment systems, and developer tooling that enable AI-powered experiences to operate reliably, securely, and at scale.

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. AWSBedrock Agent Core ) 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.

• 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.
• Strong 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 Agent Core), 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 Open Telemetry, 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.

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This posting is for proactive recruitment purposes and may be used to fill current openings or future vacancies within our organization.

• Hybrid Work Model:
  We’ve…