Finance & Strategy AI Engineer

About the Role

Samsara's Finance & Strategy team is seeking a technically skilled builder to lead the development, implementation, and maintenance of Finance’s data foundation and AI systems. Our team drives strategic decisions at Samsara — owning the forecasting, planning, analysis and reporting that leadership relies on to run the business. This role will work closely with our F&S team and partner across BizTech, PeopleOps, Accounting and beyond, acting as our technical bridge with systems owners, data engineers and the business.

You'll design, develop and operate secure, scalable applications, pipelines, automations and AI workflows that transform fragmented financial data from NetSuite, Workday, Adaptive and Salesforce into a modern Databricks foundation that powers production-grade, decision-ready systems. You will also own and support our existing Workday Adaptive Planning instance through the transition.

Responsibilities

• Own the data foundation and AI roadmap for Finance & Strategy — architecting the future state of Samsara's financial data and systems landscape, setting modeling strategy, and identifying and closing gaps in data, tools, and processes, while maintaining and evolving the existing Workday Adaptive Planning instance.
• Design, build, and maintain the pipelines and integrations connecting Samsara's financial systems (e.g., Databricks, NetSuite, Workday, Adaptive, Salesforce) to ensure seamless data flow, scalability, and reliability.
• Build Samsara's agentic-first close, and extend AI-powered tools and automations across core finance processes — forecasting and scenario planning, variance and driver analysis, headcount and workforce planning, and management reporting.
• Lead cross-functional alignment across Finance, BizTech, PeopleOps, Accounting and beyond on system workstreams that span teams — resolving competing priorities and driving shared decisions.
• Evaluate and implement emerging technologies, staying current on advancements in AI, automation, and data infrastructure, proactively identifying opportunities for innovation and efficiency.
• Formalize best practices in data modeling and infrastructure, and enable end users through documentation, training, technical support, and troubleshooting.
• Build with governance in mind — establishing data quality standards and access controls — holding the work accountable to measurable impact on close cycle time and forecast accuracy.

Minimum Requirements

• Bachelor's degree in Computer Science/Engineering, Information Systems, Finance/Accounting, or comparable work experience.
• 8+ years of relevant experience building and scaling production-grade data pipelines, integrations, and enterprise applications, with strong engineering fundamentals.
• Hands-on experience with large language model (LLM) applications, including prompt engineering, retrieval-augmented generation, agentic workflows, and evaluation.
• Proficiency coding in Python, particularly for scripting, data manipulation, and interacting with APIs.
• Experience with SQL databases, including data modeling and query optimization.
• Experience with data platforms and warehouses (e.g., Databricks, Snowflake, BigQuery, Redshift), and with enterprise systems (e.g., NetSuite, Workday, Adaptive, Salesforce, Google Suite, Slack).
• Working knowledge of financial planning, forecasting, and close processes.
• Excellent collaboration and communication skills with both technical and non-technical stakeholders.

Preferred Qualifications

• Strong problem-solving mindset and curiosity about applying AI to finance processes.
• Experience building agentic systems in production — orchestration frameworks, tool use, and evaluation techniques beyond prompt engineering.
• Experience in a high-growth or public company finance environment.
• Ability to thrive in a fast-growing environment with high degrees of ambiguity.