Agentic Finance Engineer

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

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

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

3+ years of experience spanning finance operations, data engineering, analytics engineering, data science, or a combination — with a track record of shipping reliable systems in high-growth environments

Understand the data needs of finance and corporate operations, including accounting, finance operations, FP&A, strategic finance, and procurement

You should be very proficient in SQL and Python. While you can learn data & workflow orchestration tools on-the-job, we expect you to have a very strong computer science fundamentals.

A builder's instinct: you take ownership of problems, move fast, and know when to do things properly versus pragmatically

Excellent communication skills — you can explain a data model to a CFO and a pipeline architecture to an engineer

Experience navigating ambiguity in early-stage or rapidly scaling environments

Hands-on experience deploying AI agents or LLM-powered tools

Experience with financial data governance and audit readiness

Background in strategic finance, accounting, FP&A, or finance transformation — or time spent in a high-growth tech company's finance function