Software Engineer – AI; DevOps

Staff Software Engineer – AI (Dev Ops)

Thomson Reuters is looking for a Staff Software Engineer – AI (Dev Ops) to partner closely with product, architecture, and engineering teams to define needs and technical strategy, lead research & development within the project life cycle, provide technical analysis and design, and support operations staff in executing, testing, and rolling out solutions.

• Architect and implement AI‑driven solutions using agentic AI patterns, including MCP server architectures, orchestration workflows, and agentic pipelines.
• Design and operate scalable, secure, and cost‑efficient AI platforms on cloud infrastructure (Azure and/or AWS) with Kubernetes as the primary runtime.
• Integrate LLMs, vector search, and retrieval‑augmented generation (RAG) patterns using services such as Azure AI Foundry and Azure AI Search.
• Define and implement AI/ML Ops practices for model and pipeline lifecycle, including versioning, monitoring, evaluation, and governance.
• Plan, deploy, and maintain critical business applications and AI services in production and non‑production cloud environments.
• Design and implement appropriate environments for those applications and services; engineer robust release management procedures and provide production support.
• Build and maintain CI/CD pipelines using MCPS tooling (e.g., Azure Dev Ops, Jenkins, Git Hub Actions), including automation for building, testing, scanning, and deploying AI and non‑AI workloads.
• Design and maintain infrastructure‑as‑code (Terraform, Bicep, Ansible) for cloud, Kubernetes, networking, and platform services.
• Develop and maintain agentic workflows that orchestrate tools, services, and data sources to support complex business processes.
• Use AI tools within the development lifecycle (e.g., AI‑assisted code generation, Git Hub Actions AI features, AI‑driven test generation and triage) to increase velocity while maintaining quality and compliance.
• Collaborate with product and engineering teams to identify opportunities for AI automation in build, test, deployment, and operations workflows.
• Drive improvements to processes and design enhancements to automation to continuously improve production environments (reliability, observability, performance, cost).
• Perform daily system monitoring, verifying integrity and availability of services, reviewing system and application logs, and verifying completion of scheduled and automated tasks.
• Perform ongoing performance tuning, infrastructure upgrades, and resource optimization as required.
• Provide Tier II/Tier III support for incidents and requests from various constituencies; lead technical recovery for high‑severity incidents impacting AI platforms and services.
• Establish and maintain monitoring, alerting, SLOs, and dashboards for AI services; contribute to disaster recovery planning and testing to ensure business continuity.
• Partner with security and compliance teams to ensure AI platforms and pipelines meet TR security, privacy, and governance standards.
• Provide leadership, technical support, user support, technical orientation, and technical education activities to project teams and staff across multiple locations.
• Influence broader technology groups in adopting cloud, Kubernetes, and AI technologies, processes, and best practices.
• Mentor and coach engineers (Dev, QA, Dev Ops, Data/ML) in modern Dev Ops, AI/ML Ops, and platform practices.
• Maintain and contribute to our knowledge base and documentation, including runbooks, design docs, and standards.
• Participate in and often lead technical design reviews, architecture decisions, and cross‑team initiatives.

• 8+ years of overall software engineering / Dev Ops / platform engineering experience.
• 3+ years in a Lead‑level Dev Ops / Platform / SRE capacity.
• 2+ years supporting AI‑driven solutions at enterprise scale.
• Strong experience designing and operating solutions on cloud platforms (Azure and/or AWS).
• Hands‑on expertise with Kubernetes and containerization (Docker), including managed Kubernetes (e.g., AWS EKS, Azure AKS).
• Deep knowledge and hands‑on experience with CI/CD and MCPS tools (Azure Dev Ops, Jenkins, Git Hub Actions).
• Experience…