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Vice President, AI Platform Engineering

Job in Frisco, Collin County, Texas, 75034, USA
Listing for: Thomson Reuters
Full Time position
Listed on 2026-07-15
Job specializations:
  • Software Development
    AI Engineer (Applied/Software), Software Architect, AI Reliability/ Performance Engineer
Salary/Wage Range or Industry Benchmark: 250000 - 350000 USD Yearly USD 250000.00 350000.00 YEAR
Job Description & How to Apply Below

About the Role

Thomson Reuters is investing in AI as a core capability across Legal, Tax, Risk, News, and Corporates. We are seeking a senior Technology Leader to define and drive the technical direction for how enterprise AI systems—including multiagent architectures, finetuned models, and retrieval-augmented solutions—are designed, governed, and scaled across the platform organization, while ensuring product engineering teams can safely and efficiently consume these capabilities.

This role leads a global AI Platform Engineering organization responsible for delivering AI Engineering Services. Positioned within Platform Engineering, it operates in close partnership with AI Labs, Product Engineering, Information Security, Legal, and Procurement to establish production-grade AI platforms and standards.

You will serve as the technical authority across three integrated domains:
Enterprise AI Engineering Services, AI‑Native Developer Enablement, and AI Platform Integration—ensuring cohesive, secure, and scalable adoption of AI capabilities across Thomson Reuters. This includes leading a diverse global team of 35+ engineers and driving engineering rigor, platform standardization, and responsible AI practices.

As Vice President, AI Platform Engineering
, you will report to the Head of Platform Engineering and be a key member of a high-performing organization at the center of Thomson Reuters’ technology and AI strategy. You will own:

AI‑Native Engineering and Developer Enablement

You will define what AI‑native development means at Thomson Reuters: the agreed coding‑agent stack, the prompt and evaluation standards, the CI/CD integrations, and the guardrails that make agent‑assisted development safe inside the enterprise. You will govern the AI developer tooling estate (coding agents, prototyping tools, evaluation and observability platforms) and set patterns for MCP servers and developer‑facing agents.

AI Platform and Tooling Integration

You will own the technical direction for the AI platform capabilities engineering teams across TR consume: model serving, evaluation infrastructure, RAG and retrieval infrastructure, fine‑tuning workflows, prompt and observability tooling, and the integration of these capabilities with the existing platform estate (IDP, API management, observability, Git Hub). You will partner with and align the Cloud Infrastructure agentic platform team to keep developer‑facing and ops‑facing AI strategies coherent.

Performance

& Scalability

You will own the quality bar for security, scalability, and reliability of AI Platform Systems. Define and enforce observability and performance standards for AI‑driven workloads operating at enterprise scale across millions of documents and interactions.

Collaboration & Leadership

You will lead and grow teams of AI engineers building the services and platforms that translate AI capabilities into real‑world product applications. Foster a culture of experimentation, continuous improvement, and engineering excellence. Own hiring, performance, and mentorship across the organization.

Key responsibilities and impact
  • Define, publish, and evolve TR’s AI‑native engineering standards, including reference implementations; support adoption through office hours and direct engagement with product engineering teams.
  • Partner with Info Sec, Legal, Privacy, and the AI Council to ensure AI engineering practices are auditable, compliant, and production ready.
  • Lead architecture reviews for AI systems entering the production estate, driving standards compliance and shaping the Platform Engineering portfolio ahead of demand.
  • Lead technical evaluations and build‑vs‑buy decisions for AI infrastructure, model serving, evaluation platforms, and developer tooling.
  • Represent Platform Engineering in M&A technical due diligence, where AI, cloud, and modern engineering posture are in scope.
  • Drive broader engineering productivity and developer experience initiatives where AI intersects with IDP, DORA, APIfirst delivery, and Consumer Success engagements.
  • Coach and mentor principal and staff engineers across the organisation, raising the bar for how TR designs, evaluates, and delivers…
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