Lead Engineer – AI Transformation

Role Overview

AI is at an inflection point for Ocrolus. We're looking for a builder who can turn ambiguous internal business workflows across teams into AI-driven solutions with clear, measurable outcomes. 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 business 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 Business Process AI Opportunities within the Organization
   • Partner with cross functional teams and leadership.
   • Proactively evaluate existing business 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
2. 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
3. Explore, identify, evaluate, and deploy AI solutions
   • Assess different models, tools, and workflows
   • Make the right trade-offs across models, tools, and approaches
4. 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