Cost Engineer

About NCS

NCS is a prominent AI technology services provider with a workforce of 15,000 across Asia Pacific. As a subsidiary of Singtel Group, NCS leverages a global partner network to deliver agile AI-driven technology solutions that create meaningful business results across various industries. Their approach combines AI with digital resilience for enhanced service delivery.

Role Overview

The AI FinOps Engineer will contribute to delivering cost-effective, production-ready AI solutions by tracking token consumption and inference expenditures, optimizing model usage, and implementing cost governance policies across different client projects. The position involves creating dashboards and cost reports, identifying optimization opportunities between high-cost frontier and smaller models, and assisting with cost modeling for proof of concept (POC) to production scale. Collaboration with AI Architects, LLMOps Engineers, Cloud Architects, and commercial teams is key to delivering transparent and defensible cost insights.

Senior AI FinOps Engineers take extended responsibility by establishing FinOps practices across multiple AI projects, engaging in pricing and commercial negotiations, mentoring juniors, and defining enterprise-wide AI cost governance standards.

Key Responsibilities

• Develop and manage monitoring systems for token usage and inference costs with detailed breakdowns by model, engagement, and client.
• Detect and implement right-sizing strategies to balance the use of expensive frontier models with cost-effective fine-tuned or smaller models.
• Establish cost alerting mechanisms and budget limits to prevent overspending in AI engagements.
• Support AI Architects and specialists with cost-performance evaluations during model selection, presenting comprehensive total cost of ownership analyses.
• Forecast and model costs for scaling POC to production deployments to guide financial and commercial decisions.
• Generate regular transparency reports on costs for project leads and clients, upholding FinOps best practices aligned with broader cloud financial operations.
• Contribute to both fast-paced forward deployed engineering engagements and ongoing system maintenance by providing prompt cost estimates, controlling production system expenses, and creating reusable cost modeling tools and dashboards.
• Collaborate closely with LLMOps and cloud architects on cost/performance compromises.
• Support commercial teams with accurate cost data for client discussions, without direct involvement in proposal preparation.

Role Levels and Experience

• AI FinOps Engineer: Requires 2-4 years of relevant experience. Responsibilities include maintaining cost dashboards, monitoring expenses, and analyzing model costs for select engagements under guidance.
• Senior AI FinOps Engineer: Requires 5+ years of extensive experience including prior full ownership of cloud or AI cost governance. This senior role leads FinOps frameworks, advises commercial negotiations, mentors junior staff, and sets company-wide AI cost governance policies.

Candidate Profile

• A minimum of 2 years in cloud FinOps, cost engineering, or similar technical-finance roles with familiarity in AI/ML workload cost management; 5+ years experience expected for senior roles.
• Strong understanding of large language model pricing structures including token-based, per-request, and reserved capacity models from providers such as OpenAI, Azure, AWS Bedrock, and Vertex.
• Proficient in handling cost and usage data utilizing SQL, spreadsheet analysis, and Python scripting for automation and dashboard creation.
• Capable of translating complex technical cost data into clear, non-technical narratives for stakeholders.
• Comfortable balancing quick cost estimates for proofs of concept and rigorous governance for live production systems.

Preferred Qualifications

• Certification such as FinOps Certified Practitioner or equivalent expertise in cloud cost management.
• Experience using cloud cost control tools like CloudHealth, Kubecost, and native AWS/Azure/GCP tooling adapted for AI cost monitoring.
• Knowledge of Singapore Government commercial and procurement frameworks preferred.
• Familiarity with model routing and gateway tools that track per-request costs (e.g., LiteLLM, Bedrock, Azure OpenAI).

Technical Environment

• Programming Languages: Python, SQL
• Cost & Monitoring Tools: Kubecost, AWS Cost Explorer, Azure Cost Management, GCP Billing
• LLM Cost Tracking: Model gateway routers with per-request cost metrics (LiteLLM, Bedrock, Azure OpenAI, Vertex)
• Reporting Platforms: Excel, Business Intelligence dashboards, Grafana for real-time costing visualization
• Cloud Platforms: AWS, Azure, GCP; governmental/commercial cloud exposure beneficial

Why Choose NCS?

• Engage with innovative AI products shaping tomorrow’s technology landscape
• Collaborate with diverse and skilled teams across research, engineering, and design disciplines
• Benefit from continuous professional growth and career progression opportunities
• Impact clients by turning AI research into practical solutions that address real-world challenges
• Be part of a values-driven organization emphasizing adventure, excellence, integrity, ownership, and unity
• Join an inclusive, respectful culture focused on collaboration and meaningful relationships