Principal, AI and Automation

Establish the company’s AI roadmap — prioritizing initiatives that enhance workflow efficiency, data intelligence, and customer experience. 

Stand up an Automation Center of Excellence through building a scalable foundation for centralized, AI-driven automation and workflow optimization—driving consistency, speed, and measurable value. 

Champion adoption by training internal teams and promoting best practices for responsible and effective AI usage across the organization. 

Evaluate emerging technologies in AI, LLMs, cloud-native architecture, platform design, and applied ML to continuously evolve our automation strategy and toolset. 

Build the technical and operational backbone for applied AI solutions. 

Architect, develop, and deploy AI models, agents, and automation workflows across internal systems and customer-facing products. 

Establish reusable frameworks, APIs, and pipelines to enable scalable and efficient AI delivery. 

Apply AI/ML to core processes such as SDLC (e.g., AI copilots, test automation), EDI transaction optimization, and ERP integration. 

Partner with Product and Engineering teams to ensure seamless integration of AI capabilities into the broader platform ecosystem. 

Translate AI investments into measurable outcomes. 

Identify and prioritize high-ROI and AI opportunities, building business cases and success metrics for each. Collaborate across teams to measure adoption and continuous improvement post-deployment. 

7+ years in AI engineering, machine learning, or automation. (SaaS, ERP, or supply chain technology environments preferred) 

Bachelor’s degree required (Master’s preferred) in Computer Science, AI, Data Science, or related field. 

Some travel may be involved - up to 15% 

Experience defining, executing, and scaling AI strategies across complex global organizations from the ground up 

Previous success in accelerating software delivery with AI-augmented SDLC: implementation tools and automated testing frameworks to improve development velocity and quality 

Exposure to AI use cases across multiple domains (e.g., customer onboarding, customer support, operations). 

Familiarity with LLMs, generative AI, and prompt engineering 

Strong programming in Python (additional experience with Java, C++, or similar is a plus). 

Hands-on expertise with AI/ML frameworks (TensorFlow, PyTorch, Scikit-learn). 

Proven experience deploying models via APIs, Docker, Kubernetes, and cloud-native ML platforms (AWS SageMaker, Azure ML, or Google Cloud Platform Vertex AI). 

Solid understanding of MLOps, data engineering, and software architecture principles. 

Strategic, innovative, and curious — with a passion for driving measurable business outcomes through technology. 

Exceptional communication, influence, and problem-solving abilities. Able to translate technical concepts into business impact.