AI Operations Specialist – FinOps, AI Cost Management

LGT Private Banking

AI Operations Specialist at LGT managing and optimizing AI costs across projects. Collaborating with cross-functional teams to enhance financial sustainability and efficiency in AI usage.

Posted 7/22/2026full-timeZurich • 🇨🇭 SwitzerlandJuniorMid-LevelWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in cloud cost management and AI financial operations, with a strong focus on cost efficiency, reporting, and stakeholder communication. Proficient in analyzing AI usage data to identify trends and anomalies, facilitating informed financial decisions.

Highest-signal resume keywords

Cloud Cost ManagementAI Financial OperationsCost Observability ToolsStakeholder ManagementAnalytical Skills

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

Cost ManagementAI ServicesMachine Learning EcosystemsData AnalysisBudgetingForecastingReportingKPI DevelopmentModel Right-SizingUsage Pattern Analysis

Soft Skills

Communication SkillsStakeholder EngagementProblem-Solving

Tools & Technologies

AWS SageMakerAzure AI ServicesAzure OpenAIGCPFinOps Best PracticesCost Management Platforms

Industry Keywords

AI Cost ManagementFinancial OperationsCloud InfrastructureObservabilityGovernance Standards

Tech Stack

Tools & technologies

AWSAzureCloudGoogle Cloud Platform

About the role

Key responsibilities & impact

Advise project, product and platform teams on cost-efficient and sustainable use of AI services, models and infrastructure
Track AI costs at a granular level, including API calls, token usage, model runs and infrastructure consumption
Build and maintain reporting, dashboards and forecasting models for AI workload growth, spend trends and budget utilization
Identify cost-saving opportunities through model right-sizing, improved caching strategies and better usage patterns
Monitor AI usage across native and third-party cloud cost management and observability platforms, including AWS, Azure and GCP
Review unusual consumption behavior, investigate root causes and work with developers and AI users to define corrective actions
Support planning, forecasting and budgeting for AI initiatives and help teams align expected demand with available funding
Contribute to governance, standards, KPIs and reporting for AI-related spend
Act as the bridge between Data Scientists, engineers, product teams and Finance to translate operational AI challenges into clear financial requirements and decisions
Promote awareness and adoption of FinOps best practices for AI across the organization
Collaborate with existing FinOps practitioners responsible for broader infrastructure cost management, including Azure and on-premise environments.

Requirements

What you’ll need

2–3+ years of experience in cloud cost management, program management, IT financial operations or a similar role
Good understanding of modern AI and ML ecosystems, including platforms such as AWS SageMaker, Bedrock, Azure AI Services and Azure OpenAI
Experience with cost observability and monitoring tools
Strong analytical skills and the ability to interpret usage data, identify anomalies and derive practical recommendations
Excellent stakeholder management and communication skills, with the ability to translate technical consumption data into clear financial narratives

Benefits

Comp & perks

Become part of a family – not just a company.