Agentic Finance Engineer
Builds scalable financial data infrastructure and AI-powered automation for finance operations, integrating tools like dbt, Snowflake, and agentic workflows to replace manual processes. Requires 3+ years in finance ops/data engineering, SQL/Python proficiency, and finance domain expertise.
About the job
What You'll Do
Finance Data & Systems
- Facilitate the design, build, and maintenance of a reliable financial data foundation using modern tools (e.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 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
- Very proficient in SQL and Python. 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
Bonus Points
- 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
Compensation
- Base cash comp from $175K - $250k
- Aggressive bi-annual performance bonus structure
- Generous equity grant vested over 4 years
- Up to $15k Relocation bonus
- $10K housing bonus (if you live within 0.5 miles of our office)
- $1.5K monthly stipend for meals
- Free Equinox membership
- $200 monthly laundry reimbursement
- $200 monthly personal wellness reimbursement
- Health, Dental, Vision insurance
- 401(k) with company match
Skills
SQL, Python, dbt, Fivetran, Snowflake, BigQuery, Airflow, ETL, AI Agents, LLMs
Similar jobs
Data Engineering jobs
Vanta
Remote
Own the systems that ingest, standardize, validate, and operationalize data signals for Vanta’s EPD organization. The role suits a hands-on builder who has recently shipped working tools or pipelines, uses AI-assisted development, and helps teammates grow technically.
Imprint
New York, NYBuild and operate scalable data infrastructure, including partner data sharing, identity graph foundations, and governed batch and real-time platforms. The role requires 5+ years of data, distributed systems, infrastructure, or backend engineering experience and strong cloud and data-platform expertise.
xAI
Palo Alto, CA
Build scalable data pipelines, infrastructure, and quantitative models that support experimentation, forecasting, and business decision-making. The role requires 4+ years of production data engineering experience, strong Python and SQL skills, distributed computing expertise, and a quantitative degree.
Abridge
San Francisco, CA
Builds and optimizes scalable data pipelines, storage, and OLAP databases for ML training, analytics, and product features. Requires 5+ years in data engineering, proficiency in Python/SQL/cloud platforms, and distributed systems experience.
Benchling
San Francisco, CA
Build and operate reliable, production-grade data pipelines, warehouse infrastructure, and trusted datasets supporting company-wide analytics and AI initiatives. The role requires 3+ years of production data engineering experience, strong SQL and Python skills, and experience with Snowflake, dbt, cloud infrastructure, and orchestration.