- title
- AI FinOps Engineer
- family
- agent-ops
- maturity
- emerging
- owns
- Owns cost visibility and financial accountability for AI/ML and LLM workloads: builds token- and model-level unit-cost models, tracks GenAI token usage and cloud/GPU consumption, enforces cost allocation and tagging standards, embeds cost signals into engineering pipelines, and delivers dashboards, anomaly alerts, and executive forecasting so the organization can plan and control AI spend.
- skills
[FinOps principles and cloud cost management][LLM/token-based pricing model economics and unit-cost design][cost data pipelines and dashboards (cloud cost management tooling, Power BI, Grafana)][cross-platform AI cost governance and chargeback/allocation design][data engineering (Python, SQL, PySpark)][GPU/inference cost and provisioned-throughput optimization]
- pay
low: 160000
high: 220000
currency: USD
basis: base
- seniority
- senior-ic
- distinctFrom
- Unlike agentops-engineer, where cost and latency monitoring is one of several observability/reliability duties inside a broader agent-runtime job, the AI FinOps Engineer's entire remit is the financial/economics layer: token-level unit economics, cost allocation, budgeting, and forecasting across AI workloads, a specialization pulled from cloud FinOps discipline rather than from SRE/agent-ops. Also distinct from ai-governance-lead (policy/risk, not cost) and ai-gateway-engineer (routing infrastructure, not cost accounting).
- notes
- New addition (no existing tracked id). Directly fetched and re-verified the Cargill posting myself; it resolves and the quote above is verbatim from that page ('Owns end-to-end problem areas, including design, implementation, and adoption' is a second, paraphrased-from-fetch line describing scope, not re-quoted here to avoid stitching fragments). Corroborated by a second live, directly-fetched posting: Singtel Group 'AI FinOps Engineer #AIDA' (https://groupcareers.singtel.com/job/AI-FinOps-Engineer-AIDA-Sing/1327804166/), verbatim: 'Maintain the centralized framework for tracking Azure consumption and GenAI token usage across projects, teams, and applications' and 'Build dashboards and alerts to monitor real-time and forecasted costs, including anomaly detection for budget risks.' Neither Cargill nor Singtel discloses pay. Pay ($160K-$220K USD base, NYC) is sourced instead to a third, US-based, first-party posting: Bloomberg 'AI & LLM Infrastructure FinOps Analyst' (731 Lexington Ave, NYC, job #18395, https://bloomberg.avature.net/careers/JobDetail/AI-LLM-Infrastructure-FinOps-Analyst/18395). IMPORTANT CAVEAT: direct WebFetch attempts to that Bloomberg URL, its LinkedIn mirror, and a wallstreetcareers.com mirror all failed to load for me (404 / bot-blocked), so I could NOT independently re-fetch that raw page myself; the responsibilities and the '$160,000 - $220,000 USD Annual + Benefits + Bonus' figure come from consistent search-engine snippets across three separate queries (one confirming the exact NYC office address), which is a materially weaker evidentiary basis than the Cargill/Singtel pages I fetched directly. Flagging for the validator to attempt its own fetch of the Bloomberg posting before trusting the pay figure; if it cannot resolve either, the pay field should be dropped and the entity kept unpaid (like ai-tooling-engineer / ai-gateway-engineer in the baseline). General 'FinOps Engineer' salary aggregates (ZipRecruiter ~$84K-$135K, Glassdoor ~$93K-$166K) exist but are generic cloud-FinOps, not AI-specific, and were deliberately NOT used to avoid misattributing a non-AI figure. Maturity marked 'emerging': this is a newly-forming specialization splitting off from cloud FinOps specifically for AI/token economics, first appearing in postings in 2026.
