Tech Stack

Description

You will lead the design, build, and deployment of AI workflows across Material Bank, spanning internal AI enablement and business-embedded AI to improve efficiency and drive revenue. You'll collaborate cross-functionally with technical and non-technical teams to translate business needs into production-ready AI solutions and advise executive leadership on AI strategy.

Requirements

• 5+ years of engineering experience with production-grade AI/ML systems.
• Deep hands-on experience with LLMs, embeddings, RAG architectures, and/or agent-based frameworks.
• Strong programming proficiency in Python and/or TypeScript/JavaScript.
• Experience designing scalable data pipelines and working with SQL/NoSQL databases.
• Proven ability to translate ambiguous business problems into practical, high-impact technical solutions.

Responsibilities

• Design, build, and deploy end-to-end AI workflows from concept through production.
• Identify and prioritize high-impact AI opportunities to improve efficiency and organizational velocity.
• Embed AI into core business processes including sales prospecting, material classification, and data enrichment.
• Architect scalable solutions using LLMs, embeddings, agent frameworks, and modern data infrastructure.
• Educate and advise leadership on AI capabilities, trade-offs, prioritization, and ROI.