Thomson Reuters
Staff Software Engineer – AI (DevOps)
Thomson Reuters is looking for a Staff Software Engineer – AI (DevOps) 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.
Responsibilities
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 DevOps, Jenkins, GitHub 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, GitHub 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, DevOps, Data/ML) in modern DevOps, 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.
Qualifications
8+ years of overall software engineering / DevOps / platform engineering experience.
3+ years in a Lead‑level DevOps / 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 DevOps, Jenkins, GitHub Actions).
Experience implementing and supporting MCP server architectures, orchestration workflows, and agentic pipelines in production environments.
Demonstrated experience with AI/ML Ops concepts and tooling.
Strong scripting and programming skills in Python, Bash, and/or PowerShell.
Practical experience with Infrastructure as Code (Terraform, Bicep, Ansible).
Experience with Azure AI Foundry and Azure AI Search, or similar AI platform and vector search technologies.
Solid understanding of Git, branching strategies, and GitOps principles.
Proven experience owning and operating continuous delivery / continuous deployment pipelines and production services.
Strong communication and collaboration skills, with experience influencing across teams and mentoring other engineers.
Nice to Have
Experience building and deploying .NET Core and/or Java‑based solutions in cloud and Kubernetes environments.
Strong understanding of API‑first design and implementation.
Experience implementing comprehensive testing strategies (unit, integration, performance, chaos) for AI systems.
Prior experience setting up monitoring tools (Prometheus, Grafana, CloudWatch, Azure Monitor, OpenTelemetry) and disaster recovery plans.
Exposure to data and ML tooling (feature stores, experiment tracking, model registries).
Experience working in regulated or compliance‑sensitive environments.
What’s in it For You
Hybrid Work Model: flexible 2‑3 days per week in the office.
Flexibility & Work‑Life Balance: Flex My Way policy, work from anywhere up to 8 weeks per year.
Career Development: Grow My Way programming and continuous learning.
Industry‑Competitive Benefits: vacation, mental‑health days, Headspace app, retirement savings, tuition reimbursement, incentive programs.
Culture: inclusive, flexible, work‑life balance, values of customer obsession, win, challenge, fast learning, stronger together.
Social Impact: two paid volunteer days per year and ESG initiatives.
About Us Thomson Reuters informs the way forward by bringing together trusted content and technology for professionals across legal, tax, accounting, compliance, government, and media. We serve professionals with highly specialized software and insights to make informed decisions and pursue justice, truth, and transparency.
Equal Employment Opportunity Thomson Reuters is an equal‑employment‑opportunity employer. We welcome applicants of all backgrounds and comply with all applicable laws. We do not discriminate on the basis of race, color, sex, gender identity, sexual orientation, religion, disability, national origin, age, veteran status, or any other protected characteristic.
Base Compensation For eligible US locations, the base compensation range for this role is $147,000 USD – $273,000 USD. Additional compensation may include an annual bonus.
Seniority level Mid‑Senior level
Employment type Full‑time
Job function Engineering and Information Technology
Industry Software Development
#J-18808-Ljbffr
Responsibilities
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 DevOps, Jenkins, GitHub 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, GitHub 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, DevOps, Data/ML) in modern DevOps, 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.
Qualifications
8+ years of overall software engineering / DevOps / platform engineering experience.
3+ years in a Lead‑level DevOps / 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 DevOps, Jenkins, GitHub Actions).
Experience implementing and supporting MCP server architectures, orchestration workflows, and agentic pipelines in production environments.
Demonstrated experience with AI/ML Ops concepts and tooling.
Strong scripting and programming skills in Python, Bash, and/or PowerShell.
Practical experience with Infrastructure as Code (Terraform, Bicep, Ansible).
Experience with Azure AI Foundry and Azure AI Search, or similar AI platform and vector search technologies.
Solid understanding of Git, branching strategies, and GitOps principles.
Proven experience owning and operating continuous delivery / continuous deployment pipelines and production services.
Strong communication and collaboration skills, with experience influencing across teams and mentoring other engineers.
Nice to Have
Experience building and deploying .NET Core and/or Java‑based solutions in cloud and Kubernetes environments.
Strong understanding of API‑first design and implementation.
Experience implementing comprehensive testing strategies (unit, integration, performance, chaos) for AI systems.
Prior experience setting up monitoring tools (Prometheus, Grafana, CloudWatch, Azure Monitor, OpenTelemetry) and disaster recovery plans.
Exposure to data and ML tooling (feature stores, experiment tracking, model registries).
Experience working in regulated or compliance‑sensitive environments.
What’s in it For You
Hybrid Work Model: flexible 2‑3 days per week in the office.
Flexibility & Work‑Life Balance: Flex My Way policy, work from anywhere up to 8 weeks per year.
Career Development: Grow My Way programming and continuous learning.
Industry‑Competitive Benefits: vacation, mental‑health days, Headspace app, retirement savings, tuition reimbursement, incentive programs.
Culture: inclusive, flexible, work‑life balance, values of customer obsession, win, challenge, fast learning, stronger together.
Social Impact: two paid volunteer days per year and ESG initiatives.
About Us Thomson Reuters informs the way forward by bringing together trusted content and technology for professionals across legal, tax, accounting, compliance, government, and media. We serve professionals with highly specialized software and insights to make informed decisions and pursue justice, truth, and transparency.
Equal Employment Opportunity Thomson Reuters is an equal‑employment‑opportunity employer. We welcome applicants of all backgrounds and comply with all applicable laws. We do not discriminate on the basis of race, color, sex, gender identity, sexual orientation, religion, disability, national origin, age, veteran status, or any other protected characteristic.
Base Compensation For eligible US locations, the base compensation range for this role is $147,000 USD – $273,000 USD. Additional compensation may include an annual bonus.
Seniority level Mid‑Senior level
Employment type Full‑time
Job function Engineering and Information Technology
Industry Software Development
#J-18808-Ljbffr