Senior AI FinOps Engineer #AIDA

Powering the Future with AIDA AIDA - Intelligence meets Impact. At AIDA (Artificial Intelligence & Data Analytics), you will design and scale AI and data solutions that power Singtel’s transformation into a global, AI-first telco of the future. Together, we will redefine the telecommunications industry in a culture where intelligence empowers people, and human potential sits at the heart of everything we do. Be a Part of Something BIG! Own the FinOps framework for Central AI Kitchen, providing full visibility and control of cloud, on-prem OpenShift, GPU infrastructure and GenAI token consumption Drive optimization of AI token usage, GPU/compute utilization and OpenShift resources to achieve sustainable unit economics while meeting application performance requirements Establish chargeback/showback, cost allocation and governance standards to ensure accurate attribution of platform costs to projects, teams and applications Administer platform budgets, forecasts and procurement plans, proactively identifying budget risks, cost anomalies and capacity requirements Partner engineering, infrastructure, procurement and finance teams to continuously optimize cloud and on-prem infrastructure costs Champion FinOps best practices across AIDA, ensuring AI platform investments are aligned with utilization, business value and financial efficiency How You will Make An Impact: Own and maintain the centralized FinOps framework for tracking cloud, OpenShift, GPU infrastructure and GenAI token consumption across projects, teams and applications Drive GenAI token cost optimization through model selection, routing, caching, prompt/token efficiency, usage controls and analysis of cost per request/use case Optimize OpenShift infrastructure consumption through resource right-sizing, utilization analysis, workload scheduling, quota management and identification of under-utilized CPU, memory, storage and GPU resources Drive cloud cost optimization across Azure services through right-sizing, reservation/commitment planning, workload scheduling, storage optimization and elimination of idle or unnecessary resources Establish and operate chargeback/showback models, tagging, cost allocation and governance standards for accurate project and use-case level attribution Administer Central AI Kitchen operating and infrastructure budgets, including forecasting, budget tracking, variance analysis and regular management reporting Support infrastructure, software and cloud procurement activities including demand forecasting, quotation evaluation, commercial analysis, contract/commitment planning and purchase requirements Build dashboards, alerts and unit-cost metrics to monitor actual and forecasted spend, utilization, token cost and cost efficiency, including anomaly detection for budget risks Partner Platform Engineering, ML/LLMOps, IT Infrastructure, Finance and Procurement teams to identify and implement cost optimization opportunities without compromising platform performance and reliability Drive adoption of FinOps practices across Central AI Kitchen and provide recommendations to management on investment, capacity, sourcing and cost optimization decisions. Skills for Success: Bachelor’s degree in Computer Science, Engineering, or a related field At least 6 years of experience in cloud infrastructure, platform engineering, FinOps, technology cost management and/or related operations Hands-on experience managing and optimizing cloud infrastructure costs, including budgeting, forecasting, cost allocation and commercial commitments Experience working with Kubernetes/OpenShift environments and analyzing infrastructure resource utilization and cost Experience partnering Finance, Procurement and engineering teams on technology budgets, procurement and cost optimization Strong knowledge of cloud FinOps practices including budgeting, forecasting, cost allocation, chargeback/showback, anomaly management and unit economics Working knowledge of Kubernetes/OpenShift resource management including CPU, memory, storage and GPU utilization, requests/limits, quotas and workload scheduling Knowledge of Kubernetes/OpenShift cost management tools such as Kubecost/OpenCost and observability platforms such as Grafana Understanding of GenAI/LLM cost drivers including input/output tokens, model serving, GPU utilization, context size, model routing and inference economics Ability to analyse AI token consumption and identify optimization opportunities across prompts, models, applications and LLM endpoints Experience developing dashboards and management reports using Grafana or equivalent tools Experience in technology budgeting, procurement analysis, vendor quotations and commercial/cost modelling Strong communication skills to explain technical cost drivers in business-oriented language Problem-solving and innovation mindset to find creative ways to balance performance vs cost in AI workloads Are you ready to say hello to BIG Possibilities? Join Singtel to shape what's next and accelerate your career through meaningful work, continuous learning, and real impact. Take the leap with Singtel to shape what’s next and accelerate your growth.