AI Operations Engineer - Supply Chain

Quantum Corp. leads the world in helping users collaboratively solve some of the world's hardest computer challenges. Whether its wrangling Petabytes of data for cutting edge movie production, managing global content production workflows, exploring new sources of energy, or managing oceans of content and blending collaborative high-speed workflows with cutting-edge object storage, Quantum has the tools and technology to help you engineer the solution that works now - and preserves your work for decades to come.

We are seeking a hands-on AI Operations Engineer to drive end-to-end optimization of our supply chain and operational processes. This is a builder role, focused on identifying inefficiencies, designing AI‑driven solutions, and deploying automation across planning, manufacturing, logistics, and service workflows.

This role sits at the intersection of operations, data, and automation, with a mandate to eliminate manual work, improve system performance, and continuously optimize how the business runs.

Key Responsibilities

• Identify and fix process inefficiencies across supply chain, manufacturing, and service operations using data and firsthand workflow analysis
• Design and deploy AI-driven automation to replace manual, repetitive tasks and improve decision-making
• Build and integrate solutions across ERP, planning, and operational systems
• Develop and operationalize AI/ML models and workflows, including data pipelines, automation scripts, and intelligent agents
• Rapidly prototype and scale solutions, turning ideas into production-ready systems that deliver measurable impact
• Monitor and optimize system performance, continuously improving accuracy, throughput, and cost efficiency
• Collaborate directly with operations teams to redesign workflows and embed AI into day-to-day execution
• Diagnose root causes of operational issues and implement durable, system-level fixes
• Track impact through KPIs (cost reduction, cycle time, service levels, productivity)

Qualifications / Profile

• 5-8+ years of similar work
• Strong hands-on experience in automation, data engineering, or AI/ML applied to operations
• Proven ability to build and deploy production solutions, not just analysis or dashboards
• Experience integrating AI with enterprise systems (ERP, supply chain, manufacturing, service platforms)
• Strong skills in Python, APIs, data pipelines, and automation tools
• Solid understanding of supply chain or manufacturing operations
• Highly analytical, practical, and execution-driven
• Comfortable working across functions and fixing real-world operational problems
• Willing and able to work from our Centennial, CO office during core business hours at a minimum (Tuesday - Thursday 10am-4pm)

What Success Looks Like

• Manual workflows eliminated or fully automated
• Planning and execution decisions improved through AI-driven insights
• Reduced cycle times, lower cost, and higher service performance
• Scalable systems that continuously improve operations over time

Why This Role Matters

AI and automation are transforming operations by enabling real-time decision-making, reducing inefficiencies, and optimizing workflows across the supply chain. This role is critical to turning that potential into measurable business impact.

Quantum provides a diverse portfolio of health plans for medical and prescription, dental, vision, life, disability and supplemental medical insurance options. We also support our team members' efforts to develop and maintain a healthy lifestyle through reimbursement and educational programs. Quantum offers a company-matched 401(k) plan to help employees save for retirement in a tax-advantaged way. We also have an Employee Stock Purchase Program for purchasing Quantum stock at a discounted rate. 

Anticipated Annual Salary Range: $100,000 - $135,000 for qualified applicants.  

The above pay range represents Quantum's good faith and reasonable estimate of possible compensation at the time of posting. Pay within or outside of the range will be based on a variety of factors, including but not limited to, relevant experience, knowledge/education, skills/abilities, internal equity, and budgetary considerations.