Cost Operations Lead

FinOps Weekly; India; Hybrid; INR 4,000,000 - 7,000,000; Full time

Job summary

Glean in India is looking for a Cost Operations Lead based in Bangalore to coordinate cloud and AI/LLM cost work end to end, set the operating rhythm, remove blockers, and ensure savings are delivered within a provider-neutral stack across engineering. This hybrid role works with engineering partners to improve spend visibility and allocation discipline.

You will drive efficiency programs, scale automation, and maintain cost governance with real-time attribution and postmortem analysis to

Qualifications

• 8+ years in infrastructure, SRE, developer productivity, or platform engineering.
• 3+ years leading cross-team programs or teams.
• Deep hands-on knowledge of cloud infrastructure and AI/LLM economics.
• Experience leading efficiency, capacity, or FinOps-adjacent programs.
• Strong operational mindset, with familiarity with SLOs, error budgets, telemetry, and postmortems.
• Strong SQL and data skills.
• Ability to query BigQuery, build a Sigma workbook, and model scenarios.

Responsibilities

• Own the portfolio of cost initiatives and drive them through to completion.
• Coordinate cloud and AI/LLM efficiency programs across engineering.
• Validate savings after launch and identify regressions that reduce prior gains.
• Establish clear cost ownership through tagging and allocation across services, teams, customers, and features.
• Oversee LLM provider spend, including procurement and commitment sizing.
• Manage internal AI tooling spend through per-user visibility, quotas, and value review.
• Build real-time cost attribution, anomaly detection, alerting, and automated triage.
• Scale the program through automation for cost triage, regression detection, and self-serve attribution.

Job description

Cost Operations Lead

About the Role

Glean is hiring a Cost Operations Lead to coordinate cloud and AI/LLM cost work end to end. The role exists to keep a single prioritized portfolio moving, set the operating rhythm, remove blockers, and make sure savings are delivered. The work supports a provider-neutral stack with multiple efficiency programs running in parallel across engineering. It partners with engineering owners to improve spend visibility, strengthen allocation discipline, manage LLM and internal AI tooling spend, and prevent cost regressions from eroding prior gains. This is a hybrid role based in Bangalore, with three days a week in the office.

Key Responsibilities

• Own the portfolio of cost initiatives and drive them through to completion.
• Coordinate cloud and AI/LLM efficiency programs across engineering.
• Validate savings after launch and identify regressions that reduce prior gains.
• Establish clear cost ownership through tagging and allocation across services, teams, customers, and features.
• Oversee LLM provider spend, including procurement and commitment sizing.
• Manage internal AI tooling spend through per-user visibility, quotas, and value review.
• Build real-time cost attribution, anomaly detection, alerting, and automated triage.
• Scale the program through automation for cost triage, regression detection, and self-serve attribution.

Required Skills

• 8+ years in infrastructure, SRE, developer productivity, or platform engineering.
• 3+ years leading cross-team programs or teams.
• Deep hands-on knowledge of cloud infrastructure and AI/LLM economics.
• Experience leading efficiency, capacity, or FinOps-adjacent programs.
• Strong operational mindset, with familiarity with SLOs, error budgets, telemetry, and postmortems.
• Strong SQL and data skills.
• Ability to query BigQuery, build a Sigma workbook, and model scenarios.

FinOps Responsibilities

• Maintain a single prioritized view of all cost initiatives.
• Turn cloud and AI/LLM spend into measurable efficiency and margin gains.
• Confirm that expected savings are achieved after launch.
• Detect and address cost regressions before they erode prior results.
• Implement granular cost allocation and ownership across services, teams, customers, and features.
• Plan and manage LLM provider spend, including procurement and commitment sizing.
• Govern internal AI tooling spend with user-level visibility, quotas, and value assessment.
• Build real-time cost telemetry, anomaly detection, alerting, and automated triage.

Cloud Platforms & Technologies

• Programming Languages - SQL
• FinOps Platforms - LLM Gateway
• Data & Analytics - BigQuery
• Reporting & BI - Sigma

Benefits

• Compensation is set based on location, level, job-related knowledge, skills, and experience.
• Some roles may also be eligible for variable compensation, equity, and benefits.

Why You Might Be Interested

This role combines infrastructure discipline, data analysis, and financial accountability in one position. It offers direct ownership of cloud and AI/LLM cost operations, with clear responsibility for savings realization and margin improvement. The scope also includes building the automation and observability needed to scale the program. Candidates with strong FinOps-adjacent or platform engineering experience may find the cross-team impact especially meaningful.