Описание

Research, build, and maintain unit economic models, tracking token consumption patterns, input/output cost balances, and batch API efficiency across major AI providers.
Evaluate cost vs. performance trade-offs across AI model tiers (frontier LLMs vs. specialized SLMs, open-source vs. commercial APIs) and implement strategies like prompt caching, dynamic routing, and batch processing.
Design and build automation scripts, CI/CD budget checks, and internal tooling to monitor real-time AI spending and enforce cost guardrails.
Architect and deploy automated AI agents to continuously monitor infrastructure, identify token bloat, and execute proactive cost-reduction workflows.
Establish real-time alerting systems and anomaly detection models to immediately flag token consumption spikes and runaway agent loops.
Partner with Backend Engineering, Research, and Product teams to embed internal cloud cost governance and cost-conscious design principles into our AI architecture.

Minimum of 3 years of experience as a FinOps Engineer, preferably for a SaaS company.
Solid foundation and hands-on experience in cloud environments (AWS, Azure, or GCP).
Cost management experience and financial analysis and modeling.
Hands-on experience with AI foundation model APIs, token billing structures, and compute/GPU allocation models.

Full professional fluency (written and verbal) in both Hebrew and English.
Excellent interpersonal skills and ability to work effectively with people at all levels in the organization.
Independent self-learner who is comfortable working both independently and as part of a team.

FinOps Engineer