Strategic Finance Lead — AI Infra & Token Economics

Atlassian; Seattle (WA); Hybride; USD 168 000 - 220 000; Plein temps

Avantages offerts par ce poste

Benefits eligible

Bonuses & equity

Flexible work options

Résumé du poste

At Atlassian, we are seeking a seasoned Finance professional to own FP&A for our Central AI infrastructure and token economics. You will lead forecasting, budgeting, and modeling to inform investment and product decisions, partnering with Engineering, Product, and BizOps.

The role requires deep understanding of AI economics, data analytics, and cost drivers, with the ability to translate complex numbers into actionable leadership briefings in a dynamic environment.

Qualifications

• 10+ years of experience in finance modeling, driver-based forecasting, budgeting and long-range planning.
• Experience in software/cloud infrastructure cost drivers and translates into financial outcomes.
• Experience with LLM/token economics or comparable consumption-based models.
• Strong analytical judgment and ability to identify the few variables that matter in large datasets.
• Ability to operate independently through ambiguity and bring structure to unstructured problems.

Responsabilités

• Serve as a strategic Finance business partner for Central AI, influencing investment and operating decisions.
• Own financial planning and modeling for AI infrastructure and token spend, including forecasting, annual planning, long-range planning, and scenario analyses.
• Develop understanding of AI economics, token consumption, model mix, infrastructure requirements, vendor pricing, and margins.
• Drive process improvements, scalable financial models and data tooling with FinOps.

Connaissances

Financial modeling

Forecasting

Scenario analysis

Executive communication

Ambiguity management

Cloud Finops

Outils

Cloud Finops

Description du poste

At Atlassian, we are seeking a seasoned Finance professional to own FP&A for our Central AI infrastructure and token economics. You will lead forecasting, budgeting, and modeling to inform investment and product decisions, partnering with Engineering, Product, and BizOps.

The role requires deep understanding of AI economics, data analytics, and cost drivers, with the ability to translate complex numbers into actionable leadership briefings in a dynamic environment.