Lead Platform Engineer

Thomson Reuters is building the platform that powers CoCounsel's AI agent ecosystem. The Lead Platform Engineer will provide technical leadership for critical platform capabilities, shaping architecture and ensuring the reliability of systems that support AI workflows while collaborating with various teams to foster AI-driven innovation.

Responsibilities:

• 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

Requirements:

• 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 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