Agentic Finance Engineer

Mercor
San Francisco$175k – $250kPosted 19 April 2026

Job Description

Agentic Finance Engineer ABOUT MERCOR Mercor is defining the future of work. We partner with leading AI labs and enterprises to provide the human intelligence essential to AI development. Our vast talent network trains frontier AI models in the same way teachers teach students: by sharing knowledge, experience, and context that can't be captured in code alone. Today, more than 30,000 experts in our network collectively earn over $2 million a day. Mercor is creating a new category of work where expertise powers AI advancement. Achieving this requires an ambitious, fast-paced and deeply committed team. You’ll work alongside researchers, operators, and AI companies at the forefront of shaping the systems that are redefining society. Mercor is a profitable Series C company valued at $10 billion. We work in-person five days a week in our San Francisco, NYC, or London offices. ABOUT THE ROLE This is a rare, foundational hire: Mercor's first Agentic Finance Engineer. You'll sit at the intersection of finance, data engineering, and applied AI — building the systems and infrastructure that power how our finance and corporate operations team runs. You will design and deploy the modern data and automation stack from the ground up: architecting scalable financial data models, integrating AI agents into real workflows, and turning manual, spreadsheet-driven processes into reliable, production-grade systems. The ideal candidate has deep finance domain knowledge — you understand how the books actually close, how procurement flows, how revenue is recognized — and the technical fluency to translate that understanding into durable, automated systems. You're equally comfortable in a SQL editor and in a conversation with the CFO, and you're energized by building in a zero-to-one environment. WHAT YOU'LL DO Finance Data & Systems - Facilitate the design, build, and maintenance of a reliable financial data foundation using modern tools (.g. dbt, FiveTran, Snowflake/BigQuery, Airflow), covering revenue, AP/AR, procurement, close, strategic finance and FP&A - Partner closely with data infrastructure team to build Mercor's financial data model: define canonical datasets, dimensional schemas, and the transformation logic that serves Finance stakeholders - Partner with Finance leads across accounting, strategic finance, and operations to translate business requirements into technical architecture - Build and maintain dashboards and self-serve reporting tools that give finance leaders real-time visibility into key metrics AI & Automation - Own the Agentic Finance roadmap – prioritizing use cases and driving features from ideation to deployment - Identify high-value automation opportunities across Finance and corporate operations — month-end close tasks, reconciliations, procurement workflows, variance analysis — and ship solutions that eliminate manual work - Build intelligent, reliable automation via agents (in partnership with engineering teams), AI-powered tools, and multi-step ETL jobs into live finance workflows, using APIs (including frontier models) - Build internal tooling that Finance teams actually use: lightweight apps, workflow automations, and AI-assisted processes that save meaningful time at scale - Stay at the frontier of what's possible with AI in Finance (meeting other finance teams, reading research, etc.), and proactively bring new capabilities to bear on Mercor's highest-leverage operational problems Governance, Quality & Scale - Enforce data integrity standards and testing practices across all financial data products — ensuring auditability and reliability for a maturing Finance function - Ensure AI-assisted processes meet appropriate governance and controls standards, with clear auditability of model outputs used in financial workflows - Champion a culture of data quality and documentation so that Finance teams trust and rely on the systems you build WHAT WE'RE LOOKING FOR - 3+ years of experience spanning ... (truncated, view full listing at source)
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