[Hiring] Senior FinOps Analyst @In All Media Inc

Role Description

In this role, you will serve as the primary Cloud Economics partner for high-spend Research & Development (R&D) engineering groups operating across the APAC region. You will drive cloud financial operations, analyze complex usage datasets across major cloud providers (AWS, GCP, Azure), and manage the growing costs associated with modern AI/LLM workloads. By bridging finance and engineering, you will foster cost-conscious development practices, perform granular root-cause analyses on spend anomalies, and ensure proactive cost governance without slowing down technical innovation.

Key Responsibilities

• Engineering Advisory & Partner-Facing Consultation: Serve as the primary Cloud Economics partner for high-spend R&D engineering groups across APAC, fielding inbound queries via Slack/asynchronous channels and providing strategic, real-time guidance on architectural cost impacts.
• Anomaly Detection & Root-Cause Analysis (RCA): Proactively detect cloud and Generative AI/LLM spend spikes; conduct structured investigations isolating volume surges from unit rate fluctuations; publish detailed, written RCA reports and remediation playbooks tracked within Jira.
• Micro-Forecasting & Projections Alignment: Drive the monthly team-level (micro) forecasting process by partnering with engineering leads to reconcile central financial models against upcoming product roadmaps, deployment plans, and architectural shifts.
• LLM & Modern Workload Governance: Monitor, analyze, and attribute costs stemming from OpenAI, foundation models, and vector database workloads, modeling variable cost behaviors to prevent budget overruns.
• Showback Delivery & Reporting: Build and deliver recurring cloud showback reports for top-spending engineering organizations, highlighting cost drivers, efficiency trends, and savings opportunities.
• Cost Awareness & Knowledge Base Curation: Audit, structure, and update internal documentation, runbooks, and wiki spaces to democratize FinOps principles and educate software engineers on cost-conscious development practices.
• Project Investment Modeling: Construct bottom-up cost models for new engineering initiatives, migrations, or proof-of-concept projects to forecast long-term infrastructure overhead.

Qualifications

• Mandatory SQL Assessment Clearance: Candidates must complete an analytical SQL assessment utilizing cloud billing/usage datasets (focusing strictly on business/financial analytical problem-solving, not data pipeline engineering).
• FinOps & Cloud Economics Track Record: Proven senior-level track record in Cloud Financial Operations (FinOps), financial modeling, and cloud usage optimization across major cloud providers (AWS, GCP, or Azure).
• Advanced Analytical SQL: Proven ability to write complex analytical queries against raw billing and granular time-series usage logs.
• Consultative R&D Engagement: Strong partner-facing skills with experience advising engineering, systems architecture, and product management teams on cloud spend without authority.
• Anomaly Investigation & Written Synthesis: Demonstrated expertise authoring thorough, professional root-cause analyses that clearly articulate technical infrastructure issues to both leadership and developers.
• Forecasting Proficiency: Practical experience running iterative bottom-up/team-level cloud cost forecasts and reconciling variances against top-down quarterly forecasts.
• AI/LLM Cost Comprehension: Familiarity with LLM/Generative AI cost drivers (token throughput, prompt vs. completion ratios, context window utilization, model tiering).
• Tooling Adaptability: Hands-on experience with modern cloud cost platforms (e.g., Datadog CCM, native cloud billing tools) and day-to-day workflow tracking tools (Jira, Confluence, Slack).
• Regional Availability: Full alignment with standard APAC business hours to support distributed engineering and product teams.

Nice-to-Have Skills

• AI/LLM Cost Governance: Specialized experience in governance policies, rate optimization, and guardrail enforcement for enterprise LLM endpoints and autonomous agent systems.
• Unit Economics Strategy: Experience defining KPI-driven unit metrics (e.g., cost per search, cost per active user, cost per inference query).
• Certified FinOps Practitioner: Formal certification from the FinOps Foundation (Certified FinOps Practitioner or Professional).

Time Zone & Collaboration

This role operates entirely during standard APAC business hours to ensure direct, real-time collaboration with regional engineering teams, leadership, and cross-functional technical stakeholders.

Language

All interviews, technical documentation, daily team syncs, and operational communications will be conducted in English.