Product Manager (Cloud FinOps)

Location: Hybrid, Tel Aviv, Israel

Company

hirify.global develops a cloud cost management platform that helps companies understand, allocate, and optimize cloud and AI infrastructure spending. The company has raised over $85M and has more than 100 employees across Tel Aviv and New York.

What you will do

• Own hirify.global's enrichment layer, joining operational metrics with cost data to explain what was spent, who caused it, and whether it was worthwhile.
• Develop Kubernetes cost allocation and efficiency capabilities across namespaces, workloads, teams, customers, idle nodes, bin packing, spot usage, and autoscaling.
• Build AI infrastructure and gateway enrichment that attributes GPU utilization and token consumption to teams, features, and individuals.
• Turn new cloud billing models, telemetry sources, and customer-scale data problems into product capabilities.
• Translate complex data questions into trusted detections and actionable recommendations for customers.
• Work directly with platform and Kubernetes specialists while shipping iteratively to enterprise customers.

Requirements

• 3+ years of experience in product roles.
• Ability to learn complex technical systems quickly, including Kubernetes scheduling, provider billing, and metrics pipelines.
• Ability to turn messy data questions into detections that customers trust enough to act on.
• Independent working style: able to investigate, unblock work, and determine next steps without waiting for prioritization or instructions.
• Comfort working with undefined, technical, data-heavy, and unsolved problems.
• Comfort being the most junior person in one discussion and the most senior in another.
• Practical experience using AI to do real work and evaluate output based on value.

Nice to have

• DevOps, SRE, or a strong data background.
• Experience shipping products that required understanding a system unfamiliar to the wider team.

Culture & Benefits

• Hybrid work environment based in Tel Aviv.
• Fast-paced startup setting with frequent replanning instead of fixed six-month roadmaps.
• Emphasis on shipping imperfect solutions quickly to enterprise customers and improving them through real usage.
• Hands-on, data-driven culture with direct collaboration with platform and Kubernetes experts.
• Use of AI coding tools and agents to accelerate prototyping and delivery.