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Stuut

Autonomous AI agent automates finance operations

Data Engineer

Data EngineeringConfirmed live in the last 24 hours
Full-timeHybrid

About the Job

Requirements

  • Have 5 or more years of hands-on experience building production data pipelines using Python.
  • Know SQL and modern cloud data warehouses; Snowflake or BigQuery experience is a plus.
  • Have deep experience implementing scalable ETL/ELT workflows using tools such as dbt, Airflow, or similar.
  • Have built or contributed to a semantic or metrics layer and care about metric consistency across surfaces.
  • Understand data modeling fundamentals and be able to design canonical schemas that normalize heterogeneous source data.
  • Have worked with real-world data from SaaS APIs, ERPs, and third-party integrations.
  • Care deeply about data quality and observability, including freshness, lineage, automated testing, and anomaly detection.
  • Have experience partnering with ML or applied AI teams on feature pipelines or supporting data infrastructure; this is a bonus, not required.
  • Have experience or strong interest in fintech, B2B SaaS, or financial data; understanding accounts receivable and accounts payable workflows is a plus.

Responsibilities

  • Build and own data infrastructure from the ground up, including designing pipelines to ingest, transform, and model data from customer ERPs, payment processors, and internal systems.
  • Build the transformation and semantic layer that serves as the single source of metric truth across customer-facing analytics, internal reporting, and AI/ML systems.
  • Design the canonical data model that normalizes information across heterogeneous source systems, with quality tests and observability built in from day one.
  • Build event and signal pipelines that turn product interactions and outcomes into clean, labeled data for analytics, machine learning, and intelligent product features.
  • Partner with product, engineering, and applied machine learning teams to embed data quality, lineage, and observability into everything shipped.
  • Implement DataOps best practices to keep data and AI features timely, accurate, and trusted.
  • Collaborate with leadership to define key performance indicators, build dashboards, and surface insights that drive strategic decisions.
  • Scale the data platform as the company grows from dozens to hundreds of customers, anticipating needs before they become bottlenecks.

Desired Qualifications

  • Experience with Snowflake or BigQuery.
  • Experience partnering with ML or applied AI teams on feature pipelines or supporting data infrastructure.
  • Experience or strong interest in fintech, B2B SaaS, or financial data; understanding accounts receivable and accounts payable workflows is a plus.

About the Company

Stuut

Autonomous AI agent automates finance operations

Stuut builds AI-powered automation tools for the finance sector. Its core product is an autonomous AI agent that handles non-strategic, repetitive tasks to speed up operations. The agent plugs into clients’ existing software stacks, making it usable across departments such as customer service and sales. Customers pay a recurring subscription to access the AI agent and its features, with optional add-on services for custom integrations and support. Compared with peers, Stuut emphasizes applying autonomous automation specifically to financial institutions and enterprises, offering seamless integration and a ready-to-use agent that reduces manual workload. The company’s goal is to help organizations run more efficiently by cutting busywork and making routine processes faster and more reliable.

Company size
51-200
Company stage
Late Stage VC
Total funding
$103M
Headquarters
New York City, New York
Founded
2024

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