Samsara
Finance & Strategy AI Engineer
$146K–$246K
San Francisco - SF9 · Full-time · Posted Aug 12, 2026
- Experience
- 8+ years of relevant experience building and scaling production-grade data pipelines, integrations, and enterprise applications.
- Education
- Bachelor's degree in Computer Science/Engineering, Information Systems, Finance/Accounting, or comparable work experience.
- Visa sponsorship
- Applicants must be able to secure and maintain the legal right to work at the company and in the specified work location, if applicable.
About the job
Build and maintain Finance & Strategy’s data foundation, pipelines, and AI systems, turning financial data into reliable tools for planning, forecasting, close, and reporting.
What you'll do
- Own the Finance & Strategy data and AI roadmap, including data modeling and support for the Workday Adaptive Planning instance.
- Build and operate integrations, pipelines, AI workflows, and automations across finance systems and processes.
- Coordinate cross-functional system work and establish data quality, access controls, documentation, and user support.
What they ask for
- Bachelor's degree in Computer Science/Engineering, Information Systems, Finance/Accounting, or comparable work experience.
- Hands-on experience with LLM applications, including prompt engineering, retrieval-augmented generation, agentic workflows, and evaluation.
- Proficiency in Python; experience with SQL databases, data modeling, and query optimization.
- Experience with data platforms and warehouses and enterprise systems; working knowledge of financial planning, forecasting, and close processes.
Nice to have
- Production experience building agentic systems, including orchestration frameworks, tool use, and evaluation beyond prompt engineering.
- Experience in a high-growth or public company finance environment.
Pay
$146,370 — $246,000 USD (annual base salary)
Tools
Python, SQL, Databricks, Snowflake, BigQuery, Redshift, NetSuite, Workday
AI focus
Build an agentic-first close and extend LLM-powered workflows and automations across forecasting, scenario planning, variance and driver analysis, workforce planning, and management reporting.
Model-written summary · the original posting is authoritative