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# AI Engineer (Remote)

- **Company:** Clevertech Partners, LLC
- **Location:** New York, NY, United States (Remote available)
- **Experience:** Experienced
- **Salary:** $70,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Airflow, Machine Learning, Tensorflow, Workflow Management Systems, Enterprise Software Applications, Chatbots, Pytorch, Apache Spark, Scikit Learn, Apache Kafka, Nintex, Data Pipelines
- **Published:** August 24, 2026
- **Apply:** https://arc.dev/remote-jobs/j/redirect/pecc9zb7hi

## About the Role

* Experience: 3-5+ years in AI/ML engineering with a track record of deploying AI into production at scale.
 * Technical Skills: Strong backend Python; expertise with ML frameworks (TensorFlow, PyTorch, Scikit-Learn, etc.); familiarity with modern data pipeline tools (Airflow, Spark, Kafka) and workflow orchestration frameworks such as n8n or LangGraph.
 * Applied AI: Background in enterprise applications such as chatbots, workflow automation, RAG pipelines, or intelligent document processing.
 * Domain Awareness: Understanding of regulated industries (financial services, insurance, or similar) with the ability to design compliance-aligned models.
 * Collaboration: Comfortable working with a lean, high-performing team and influencing technical direction.
 * Adaptability: Excels in startup-like environments with flexible, evolving tech stacks.

## Description

We're seeking experienced AI Engineers to join a high-growth fintech prospect focused on back-office workflow automation. This role is an opportunity to design and deploy production-grade AI systems for community banks, mortgage, and insurance institutions while shaping a flexible, modern architecture alongside an accomplished executive team.

What You'll Be Doing

 * Design, build, and deploy AI models into production (not just prototypes or wrappers).
 * Develop and maintain backend Python services that power intelligent automation workflows.
 * Implement enterprise-scale data pipelines for ingesting and processing financial and regulatory documents, with automated data quality checks and monitoring.
 * Train and optimize models on banking rules, compliance standards, and regulatory datasets.
 * Build intelligent routing systems (e.g., auto-approval for simple loans/accounts, escalation to humans for complex cases).
 * Collaborate with engineering leadership to shape architecture, delivery models, and stack decisions.
 * Ensure compliance-first design, embedding regulatory considerations into every product feature.


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