Head of AI & Data

eAI

$150K — $200K *
Finance & Insurance
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • 5+ years of experience with production ML/AI systems
  • Strong expertise in machine learning, data engineering or applied AI
  • Hands-on experience with large-scale datasets and model pipelines
  • Proven ability to design and deploy systems beyond just research
  • Deep understanding of model evaluation and system performance

Responsibilities

  • Lead development of AI/ML models for predictions and automation
  • Build AI agent systems utilizing LLMs and structured data
  • Establish model architecture, training, evaluation, and iteration cycles
  • Enhance model performance for accuracy, reliability, and explainability
  • Construct and scale data pipelines for real-time and batch processing
  • Design robust data architecture for structured and unstructured finance data
  • Deploy models in production ensuring reliability, scalability, and observability

Benefits

  • Opportunity to shape the core AI infrastructure for financial decisioning
  • Lead initiatives that directly influence AI application in banking
  • Work closely with the CEO/CTO, providing high-level visibility and impact
  • Influence key financial workflows through innovative AI solutions
  • Collaborate with multidisciplinary teams to drive product excellence
Full Job Description
Role Overview

We are hiring a high-impact Head of AI & Data to lead the development of AI systems powering our analytics and decisioning platform for financial institutions.

This role is responsible for building and scaling production-grade AI agents, models, and data infrastructure that operate in real-world banking environments.

You will own the technical foundation of our platform from model design to deployment ensuring our AI systems are reliable, scalable, and enterprise-ready.

What You'll Own
AI Systems & Model Development
  • 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
Data Infrastructure & Engineering
  • 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
Production Deployment & Scalability
  • 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
  • Work closely with engineering to operationalize AI features at scale
Financial Use Cases & Domain Intelligence
  • Translate financial workflows into AI-driven systems
  • Build models for use cases such as:
    • risk scoring
    • credit decisioning
    • fraud detection
    • customer behavior prediction
  • Work closely with product and domain experts to ensure real-world applicability

What We're Looking For
Required Experience
  • 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
Strong Preference For Candidates With
  • Experience with LLMs, agent-based systems, or foundation models
  • Background at leading AI, infrastructure, or data companies
  • Experience in fintech, financial data, or regulated environments
  • Exposure to scalable cloud data/ML infrastructure (AWS, GCP, etc.)
  • Experience building systems from early-stage to production scale
What Success Looks Like (First 6-12 Months)
  • Production-grade AI systems powering core financial workflows
  • Stable, scalable data infrastructure supporting multiple product lines
  • Measurable improvements in model accuracy and system reliability
  • Clear AI architecture supporting enterprise adoption and scale
  • Strong collaboration with product and engineering to ship AI features
Why This Role

This is a high-impact opportunity to build the core AI infrastructure powering decisioning and analytics for financial institutions.

You will own the technical backbone of the platform and directly influence how AI is applied in real banking environments.

Reports to: CEO / CTO

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