Role Overview:The AI Operations Strategist is a strategic advisory role within the AI Office under the Digital Transformation Office (DTO). This role is responsible for shaping the enterprise strategy for reliable, observable, cost-effective, and value-driven AI operations. The Strategist defines the enterprise direction for AIOps, AI observability, AI FinOps, operational governance, and value realization, establishing target-state capabilities, frameworks, standards, roadmaps, and success measures. The role aligns recommendations across various enterprise functions and enables implementation teams to scale and measure outcomes.
Key Responsibilities:- Define and evolve the enterprise AIOps vision, strategic principles, target-state capabilities, and operating model, establishing a multi-year AIOps capability roadmap.
- Define the enterprise AI observability and telemetry framework across model, platform, service, experience, risk, and business-value dimensions, establishing minimum observability standards and KPIs/KRIs.
- Define and govern the enterprise FinOps strategy for AI infrastructure, platforms, models, agents, and shared AI services, establishing cost-transparency principles and optimization recommendations.
- Establish AI Operations governance, including decision rights, standards, review mechanisms, and accountability boundaries, defining operational-readiness criteria for AI solutions.
- Define the enterprise framework for measuring AI operational value, reliability, cost efficiency, adoption, and business outcomes, translating insights into strategic recommendations.
- Define strategic requirements and evaluation criteria for AIOps, AI observability, telemetry, and FinOps capabilities, assessing technology options and recommending target-state capabilities.
- Serve as the strategic bridge between the AI Office and architecture, engineering, operations, finance, governance, cybersecurity, and delivery stakeholders, translating AI strategy into clear operational principles.
Required Skills:- Demonstrated experience defining enterprise strategies, operating models, governance frameworks, capability roadmaps, and transformation programs.
- Strong understanding of AI/ML operations, MLOps, model observability, reliability, telemetry, and service management.
- Strong understanding of FinOps principles, cloud economics, AI consumption models, cost allocation, forecasting, and value optimization.
- Experience translating technology, operational, and financial insights into executive-level strategic recommendations.
- Knowledge of enterprise cloud and AI ecosystems, including Microsoft Azure and Google Cloud Platform.
- Knowledge of ITSM/ITIL, SRE, SLA/SLO/XLA, incident/problem management, and operational resilience principles.
- Strong strategic thinking, executive communication, facilitation, and stakeholder-management capabilities.
Qualifications:- 10+ years of experience across enterprise technology strategy, IT operations transformation, AIOps, SRE, cloud operations, observability, or related disciplines.
- Bachelor's degree in Computer Science, Information Technology, Engineering, Data Science, Business Technology, or a related discipline.
Preferred Skills:- Experience defining enterprise AI operating models or AI transformation strategies in a complex, multi-provider environment.
- Knowledge of leading AIOps and observability ecosystems such as Dynatrace, Splunk, Datadog, Arize.AI, Azure AI, GCP Vertex AI, or equivalent platforms.
- FinOps, ITIL4, Cloud, AI/ML, SRE, or enterprise architecture certification.
- Familiarity with Agentic AI, enterprise AI platforms, MLOps, Responsible AI, and AI lifecycle governance.
- Experience developing executive transformation roadmaps and portfolio-level value-realization frameworks.
- Utility or energy-sector experience is preferred.
