Head of AI, Data

🔥 0 minutes ago

🏄 California – Remote

🏄 California – Remote

⏰ Full Time

🔴 Lead

📊 Data Scientist

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eAI

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2025

🤖 Artificial Intelligence

🏦 Banking

💳 Fintech

Artificial Intelligence • Banking • Fintech

eAI is a company that provides a governed AI infrastructure platform for regulated enterprises. The platform combines a governance engine, agent runtime, financial reasoning systems, an audit cloud, and an integration fabric to deploy autonomous AI agents safely and compliantly in production. eAI targets banks, fintechs, treasury and lending platforms, and other regulated industries with purpose-built agents for lending, treasury, compliance, risk, and operations.

📋 Description

• Lead design and development of AI/ML models for prediction, decisioning, and automation • Build AI agent systems using LLMs and structured financial data • Define model architecture, training approach, evaluation, and iteration cycles • Improve model performance across accuracy, reliability, and explainability • Build and scale data pipelines supporting real-time and batch processing • Design data architecture for structured and unstructured financial data • Ensure data quality, consistency, lineage, and security • Support integration of multiple data sources across banking workflows • Deploy models into production environments with high reliability and uptime • Ensure systems meet enterprise requirements (latency, scalability, observability) • Build monitoring systems for model drift, performance, and anomalies • Translate financial workflows into AI-driven systems • Work closely with product and domain experts to ensure real-world applicability

🎯 Requirements

• Experience building and deploying production ML/AI systems • Strong background in machine learning, data engineering, or applied AI • Experience working with large-scale datasets and model pipelines • Hands-on ability to design and ship systems (not just research) • Strong understanding of model evaluation and system performance • Experience with LLMs, agent-based systems, or foundation models (preferred) • Background at leading AI, infrastructure, or data companies (preferred) • Experience in fintech, financial data, or regulated environments (preferred) • Exposure to scalable cloud data/ML infrastructure (AWS, GCP, etc.) (preferred) • Experience building systems from early-stage to production scale (preferred)