Enterprise AI Strategy Consultant

Role: AI Operations Strategist – AIOps, AI Observability, AI Fin Ops & Enterprise AI Strategy

Location:
Rosemead, CA

Number of Positions: 3

The AI Operations Strategist is a strategic advisory role within the AI Office under the Digital Transformation Office (DTO). The role shapes the enterprise strategy for reliable, observable, cost-effective and value-driven AI operations

The Strategist defines the enterprise direction for AIOps, AI observability, AI Fin Ops, operational governance, and value realization. The role establishes target-state capabilities, frameworks, standards, roadmaps, and success measures; aligns recommendations across the AI COE, Enterprise Architecture, Cybersecurity, and Information Governance; and enables ITSM, SIAM, AIOps, MLOps, Digital Platform, and delivery teams to implement, scale, and measure outcomes.

• Define and evolve the enterprise AIOps vision, strategic principles, target-state capabilities and operating model.
• Establish a multi-year AIOps capability roadmap aligned with SCE enterprise priorities and AI transformation objectives.
• Assess current-state operational maturity, identify strategic capability gaps and recommend prioritized investments.
• Define strategic patterns for predictive operations, anomaly detection, automated remediation and AI-enabled service management.
• Guide ITSM, SRE, MLOps, Digital Platform and delivery teams in translating strategy into executable capabilities.

• Define the enterprise AI observability and telemetry framework across model, platform, service, experience, risk and business-value dimensions.
• Establish minimum observability standards, measurement principles and coverage expectations across the AI lifecycle.
• Define enterprise KPIs and KRIs for AI reliability, performance, risk, adoption, cost and business outcomes.
• Set strategic requirements for logging, tracing, telemetry, model-performance monitoring and operational insight generation.
• Guide architecture, platform, MLOps and SRE teams to align implementation with approved enterprise standards.

• Define and govern the enterprise Fin Ops strategy for AI infrastructure, platforms, models, agents and shared AI services.
• Establish AI cost-transparency principles, cost taxonomy, unit economics, allocation models and showback/chargeback strategy.
• Define cost, consumption, optimization and value KPIs for enterprise AI capabilities.
• Establish optimization principles and decision thresholds based on cost, performance, utilization, risk and business value.
• Provide strategic forecasting, investment-planning and cost-optimization recommendations in partnership with Finance, Cloud, Platform and delivery teams.
• Assess AI Fin Ops maturity and guide implementation without directly operating cost-management platforms or processes.

• Establish AI Operations governance, including decision rights, standards, review mechanisms, escalation principles and accountability boundaries.
• Define operational-readiness criteria and governance checkpoints for AI solutions entering production.
• Establish strategic standards for reliability, resilience, observability, service management and operational sustainability.
• Orchestrate alignment across AI Office, AI COE, Enterprise Architecture, Cyber, Information Governance, ITSM, SIAM, SRE, MLOps, DAS, Digital Platform and Portfolio teams.
• Identify ownership gaps, overlaps and dependencies and recommend appropriate governance interventions.

• Define the enterprise framework for measuring AI operational value, reliability, cost efficiency, adoption and business outcomes.
• Establish standardized KPI, ROI and value-attribution principles across the AI portfolio.
• Translate operational, financial and performance insights into strategic recommendations for AI Office and executive stakeholders.
• Identify portfolio-level opportunities for investment, optimization, rationalization, reuse or capability improvement.
• Provide executive insights on AI operations maturity, emerging risks, cost trends, value realization and strategic priorities.

• Define strategic requirements and evaluation criteria for AIOps, AI observability, telemetry and Fin Ops capabilities.
• Assess technology options based on interoperability, scalability, architecture alignment, governance, cost and…