Lead Platform Engineer: AI Backend & Cloud Scale

Devopsroles; Eagan (MN); Híbrido; USD 118 000 - 220 000; Tempo integral

Vantagens oferecidas por esta oferta de emprego

Hybrid Work Model

Mental Health Days

Headspace app access

Tuition reimbursement

Volunteer days

Retirement savings plan

Resumo da oferta

Thomson Reuters is seeking a Lead Platform Engineer to design and deliver scalable backend and platform services powering AI agent workflows. You will own cloud infrastructure, CI/CD, and progressive delivery, guiding cross-functional initiatives with Product, Applied AI, and Infrastructure teams.

You will mentor engineers, improve observability and reliability across Kubernetes and managed AI runtimes, and influence technical decisions in a fast-paced, AI-enabled environment.

Qualificações

• 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.

Responsabilidades

• 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. AWSBedrockAgentCore) 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.

Conhecimentos

Python

Distributed systems

Cloud-native apps

CI/CD pipelines

Observability/monitoring

AI/LLM infrastructure

Kubernetes (EKS)

PostgreSQL/Redis

Ferramentas

Kubernetes (EKS)

AWS Bedrock AgentCore

PostgreSQL

Redis

Descrição da oferta de emprego

Thomson Reuters is seeking a Lead Platform Engineer to design and deliver scalable backend and platform services powering AI agent workflows. You will own cloud infrastructure, CI/CD, and progressive delivery, guiding cross-functional initiatives with Product, Applied AI, and Infrastructure teams.

You will mentor engineers, improve observability and reliability across Kubernetes and managed AI runtimes, and influence technical decisions in a fast-paced, AI-enabled environment.