Director of AIOps

Director of AIOps

Ready to build the intelligence layer that makes global operations predictive autonomous and self-healing at Thomson Reuters

At Thomson Reuters we build technology that helps professionals pursue justice truth and transparency. We are transforming Service Management from a reactive process-bound group into a proactive intelligence-driven organization an AI-native autonomy-ready function that delivers predictive insights and automated resolutions with humans providing strategic oversight. Within our new operating model data flows into intelligence intelligence into orchestration and orchestration into execution forming a closed-Loop system in which AI is embedded in the detection decision and action loops. The AI Operations and Automation function is the intelligence layer the brain of that model.

We are seeking a Director of AIOps to lead this function responsible for developing and deploying the AI/ML capabilities and automation logic thatdrive predictive autonomic IT operations. This is one of our most important new hires: a hands-on player-coach who will lead a small team of ML automation and AIOps engineers while remaining deeply engaged in the technology. You will own the capabilities that detect issues before they impact customers correlate signal from noise and resolve incidents automatically. A central mandate is to definedrive and implement the concept of L0 a new autonomous tier in which AI and automation act ahead of the Global Command Center (GCC) reducing MTTR and preventing incidents before customer impact with human responders operating as L1 for exceptions and humans on the Loop for oversight.

About the Role

In this opportunity as Director of AIOps you will:

• Lead the newly-formed AIOps (AI Operations and Automation) function the intelligence layer or brain of our Service Management operating model building and deploying the AI/ML models and automation logic that drive predictive autonomic operations.

• Recruit build and lead a high-performing team of AIOps architects ML engineers and automation engineers remaining hands-on as a player-coach who sets technical direction by example.

• Select architect and own the AIOps platform and telemetry pipeline spanning ServiceNow Event Management correlation and enrichment and custom or third-party AIOps tooling and mature the observability practice across metrics logs traces and events instrumenting for machines rather than dashboards alone.

• Design event correlation and noise-reduction logic that collapses redundant alerts into single actionable incidents (targeting a 50% reduction in alert noise) and build anomaly-detection and predictive incident models that surface silent failures before customer impact.

• Develop automated remediation logic multi-step automations and self-healing runbooks that resolve issues without human intervention (driving a 4060% MTTR reduction for automation-eligible incidents) engineered with the rigor of production software as a centralized reusable library with testing version control and rollback readiness.

• Drive and implement the concept of L0 across Service Management establishing a new autonomous tier in which AI-driven proactive resolutions operate as L0 GCC engineers operate as L1 for exceptions and L2 is reserved for genuine major incidents and build AI-driven change risk-scoring models and LLM-based operational assistants that strengthen governance and accelerate root-cause analysis keeping humans on the loop for oversight.

• Own the AIOps roadmap and shared operational OKRs percentage of incidents auto-resolved MTTR reduction and prediction precision/recall while partnering across the Service Management operating model (Service Data and Insights Configuration and Topology Workflow Engineering and the GCC) under a clear build vs. run separation of concerns.

About You

Youre a fit for the role of Director of AIOps if your background includes proven hands-on AI enablement in operations you have deployed and operationalized AI/ML in a live operations or service management environment and can demonstrate the measurable outcomes it delivered. Specifically:

• A minimum of 10 years of industry experience in technology operations DevOps SRE or platform engineering including at least 2 years in a hands-on AIOps leadership role; bachelors degree in a technical field (Computer Science Engineering or Data Science) required with a masters and relevant certifications (cloud ML SRE ITIL or ServiceNow) preferred.

• Deep hands-on experience applying AI/ML to IT operations event correlation anomaly detection predictive incident modeling and noise reduction at enterprise scale grounded in the data science of operations (time-series analysis classification precision/recall and retraining on operational feedback).

• Fluency with AIOps platforms (e.g. ServiceNow Event Management or comparable commercial or open-source AIOps tooling) and the pipelines that ingest and enrich operational telemetry.

• Proven experience designing and scaling automated remediation orchestration and self-healing runbooks in production treated as software engineering (reusable libraries testing version control measurable toil reduction) and executed within well-designed safety guardrails such as approvals rollback and built-in observability.

• Experience establishing autonomous operating tiers such as an AI and automation L0 ahead of human responders including the decision gates readiness criteria and guardrails that make them safe to run in production.

• Strong background in observability and event management with a track record of defining and driving operational outcomes (MTTR MTTD auto-resolution rate availability/SLOs) and hands-on fluency with modern AI and agentic tooling for operations (LLM-assisted RCA agentic SRE tools) and an honest understanding of their failure modes.

• Demonstrated ability to lead and grow small high-caliber engineering and AI operations teams (AI/ML automation SRE) while remaining personally hands-on with the technical depth to earn credibility and the organizational clout and stakeholder skills to drive change across operations data governance and engineering maintaining a clear build-vs-run separation with the Global Command Center.

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