Back to Search
Overview
Principal

Principal Engineer – AI Systems & Automation

Confirmed live in the last 24 hours

Ocrolus

Ocrolus

Gurugram, Haryana, India
Remote
Posted April 20, 2026

Job Description

Come build at the intersection of AI and fintech. At Ocrolus, we’re on a mission to help lenders automate workflows with confidence—streamlining how financial institutions evaluate borrowers and enabling faster, more accurate lending decisions.

Our AI workflow and analytics platform for lenders is trusted at scale, processing nearly one million credit applications every month across small business, mortgage, and consumer lending. By integrating state-of-the-art open- and closed-source AI models with our human-in-the-loop verification engine, Ocrolus captures data from financial documents with over 99% accuracy. Thanks to our advanced fraud detection and comprehensive cash flow and income analytics, our customers achieve greater efficiency in risk management, and provide expanded access to credit—ultimately creating a more inclusive financial system.

Trusted by more than 400 customers—including industry leaders like Better Mortgage, Brex, Enova, Nova Credit, PayPal, Plaid, SoFi, and Square—Ocrolus stands at the forefront of AI innovation in fintech. Join us, and help redefine how the world’s most innovative lenders do business.

Role Overview

AI is at an inflection point for Ocrolus.

We are looking to build a strong internal AI capability at Ocrolus that improves how work gets done across the organization.

This role sits at the intersection of applied AI, systems thinking, and business transformation, with a focus on identifying, building, and scaling AI-driven solutions across internal processes.

The individual will work closely with leadership to translate AI opportunities into practical, scalable implementations.

Given the cross-functional impact, this would be a high-ownership role working closely with leadership

 

CORE RESPONSIBILITIES

  1. Identify AI Opportunities Across the Organization
  • Proactively evaluate existing processes and workflows
  • Identify areas where AI can drive efficiency, accuracy, or scale
  • Redesign workflows using an AI-first approach (current → future state)

Goal is to improve: 

  • Productivity
  • Efficiency
  • Cost
  1. Build and Implement AI Solutions
  • Design and develop AI-powered systems and workflows end-to-end
  • Apply automation frameworks and workflows to solve real problems
  • Move from idea → prototype → production deployment
  1. Drive Adoption and Influence Across Teams
  • Work across functions to enable adoption of AI-driven solutions
  • Partner with stakeholders to translate business problems into AI use cases
  • Influence without authority to ensure successful implementation
  1. Define AI Systems, Architecture & Tooling
  • Establish a scalable approach to AI systems and integrations
  • Define standards for:
    • Model selection and orchestration
    • System design and integrations
    • Tooling and frameworks
  1. Ensure Reliability, Quality & Governance
  • Ensure AI systems are reliable, secure, and production-ready
  • Define standards for:
    • Output quality and evaluation
    • Hallucination control
    • Data handling and compliance

 

WHAT SUCCESS LOOKS LIKE (FIRST 6–9 MONTHS)

  • Multiple AI-driven workflows deployed and adopted across teams
  • Measurable improvements in productivity, efficiency, or cost
  • Clear pipeline of AI opportunities across the organization
  • Established foundation for scalable AI adoption

 

WHO YOU ARE

pythongorustawsgcpaibackendiosdataanalytics