Senior Software Engineer, AI Platform

Overview

Senior Software Engineer on the AI Platform team, responsible for the reliability, scalability and long-term operational architecture of the Enterprise AI Platform at Thomson Reuters.

What you'll do

• Own and drive the long-term infrastructure strategy for the AI Platform team, designing systems and standards built to scale and reduce operational burden over time.
• Own and improve the operational posture of cloud-native services, including containerized workloads, serverless functions and managed ML infrastructure.
• Instrument services with observability tooling (Datadog, CloudWatch, or equivalent) covering metrics, logs and distributed tracing.
• Establish and enforce SLAs and error budgets; drive incident response, post-mortems and systemic reliability improvements.
• Collaborate with platform engineering to harden infrastructure against security findings (Wiz, Snyk) and maintain compliance with organizational standards.
• Design, build and maintain CI/CD pipelines for AI Platform services, SDKs and infrastructure, ensuring fast and reliable delivery across environments.
• Automate toil, including infrastructure provisioning, security remediation workflows, environment management and deployment operations.
• Mentor junior team members and raise the engineering bar across DevOps practices on the team.

What you'll need

• Strong communication skills and the ability to work across engineering, security and product teams and distill unclear requirements into clear engineering goals.
• 5+ years of experience in cloud and infrastructure engineering roles.
• Strong proficiency in Python and shell scripting, with hands-on experience building and deploying automation tools that eliminate toil and streamline DevOps workflows.
• Infrastructure-as-code experience with CloudFormation, Terraform, ARM or SAM is expected.
• Deep hands-on experience with cloud infrastructure is expected.
• Solid experience with CI/CD tooling and infrastructure deployment automation.
• Familiar with containerization (Docker, Kubernetes) and cloud-native deployment patterns.

Details

• Hybrid work model for office-based roles.