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Particle Measuring Systems

Provides contamination-control instruments for ultra-clean manufacturing

AI Enablement Lead

AI Application EngineeringConfirmed live in the last 24 hours
Full-timeNiwot, CO, USA

About the Job

Requirements

  • A bachelor's degree in information systems, computer science, or a related field, or equivalent practical experience.
  • Three to five years of experience in IT, digital enablement, or a related role, including hands-on practical experience using generative AI tools such as Copilot, ChatGPT, Claude, Gemini, Perplexity, or similar tools.
  • Experience applying change management approaches such as Prosci/ADKAR to support technology adoption, stakeholder engagement, communications, training, and reinforcement.
  • Hands-on agent and automation building experience with Microsoft Copilot Studio, Power Automate, Zapier, Make, or similar low-code platforms.
  • Ability to drive adoption and behavior change, ideally through peer- or champion-style programs.
  • Ability to facilitate and communicate effectively, including training and presenting to varied audiences.
  • Curiosity and comfort experimenting with new AI capabilities and translating them into practical business value.
  • Working knowledge of AI governance, data security, and responsible AI usage principles.
  • Experience defining and reporting productivity or return-on-investment metrics.
  • Basic scripting in Python or JavaScript for API-based automations is a strong plus.
  • Familiarity with Microsoft 365/Copilot administration, prompt engineering, or AI tool rollouts in a manufacturing or similarly regulated environment.

Responsibilities

  • Contribute to and help execute the company's AI strategy and adoption roadmap.
  • Establish and maintain guidelines for safe, secure, responsible, ethical, and lawful AI use across public and international contexts.
  • Partner with Security and the Enterprise Architect on data-handling standards and acceptable-use policies for AI tools.
  • Manage an AI use-case funnel and identify, evaluate, and prioritize opportunities to improve productivity across departments.
  • Maintain a centralized AI opportunity portfolio with intake status, business owner, expected value, risk profile, priority, and delivery progress.
  • Identify overlapping needs across departments and promote reuse of validated AI solutions to reduce duplication and accelerate value.
  • Partner with business stakeholders to scope pilots and define success metrics.
  • Build and lead an AI Champions network by recruiting, training, and supporting champions across functions to drive peer-to-peer adoption.
  • Work with teams to understand workflows, pain points, and repetitive tasks, and translate opportunities into practical AI-enabled improvements.
  • Promote AI adoption through demonstrations, success stories, templates, playbooks, and shared examples.
  • Organize AI training, upskilling programs, and a recurring community forum to share successes, use cases, and lessons learned.
  • Apply structured change management practices such as Prosci/ADKAR to build awareness, reduce resistance, support behavior change, and reinforce sustained AI-enabled work practices.
  • Serve as the organization's visible AI advocate and foster an AI-forward culture.
  • Support teams in using AI and automation to improve efficiency, quality, and customer experience.
  • Oversee end-to-end delivery of AI projects, including technical development, testing, change management, and implementation.
  • Serve as the hands-on technical expert for productivity AI tools, including Copilot, ChatGPT, Perplexity, and emerging tools.
  • Evaluate new AI tools and features and recommend adoption, configuration, and rollout approaches.
  • Track productivity and quality outcomes, including time saved, cycle-time improvement, adoption levels, user satisfaction, and measurable business impact.
  • Capture lessons learned from pilots and use them to improve future AI enablement efforts.
  • Build and deploy simple AI agents and workflow automations using low-code/no-code platforms such as Copilot Studio, Power Automate, Zapier, or Make, and light scripting against AI APIs.
  • Prototype internal automations such as document summarization, ticket triage, and meeting follow-ups, then hand off validated use cases for broader rollout.
  • Escalate use cases requiring production-grade architecture, custom retrieval-augmented generation, or complex agent orchestration to the Enterprise Architect for scoping as a separate initiative.
  • Define adoption and productivity metrics, including tool usage, hours saved, and use cases in production, and report monthly outcomes to IT leadership.
  • Track AI program spending against measurable business value to support EBITDA-focused investment decisions.
  • Continuously evaluate processes for improvements in efficiency, quality, and safety.

Desired Qualifications

  • Basic scripting in Python or JavaScript for API-based automations.
  • Familiarity with Microsoft 365/Copilot administration, prompt engineering, or AI tool rollouts in a manufacturing or similarly regulated environment.

About the Company

Particle Measuring Systems

Provides contamination-control instruments for ultra-clean manufacturing

Particle Measuring Systems (PMS) provides instruments and expertise to control contamination in ultra-clean manufacturing environments, such as pharmaceutical and semiconductor production. Its products include laser particle counters, particle spectrometers, and comprehensive Facility Monitoring Systems that count and measure airborne particles to monitor cleanrooms and other controlled spaces. The devices collect data on particle size and concentration, perform real-time monitoring, and trigger alarms to help maintain contamination-free conditions. PMS differentiates itself through a long history dating back to 1972, a spaceflight heritage, a broad patent portfolio, and its role as a global provider of established, gold-standard monitoring solutions within a larger productivity-focused group (Spectris). Its goal is to help manufacturers keep clean facilities, improve product quality and yield, and reduce risk by providing reliable, scalable contamination-control tools and expertise.

Company size
501-1,000
Company stage
Not listed
Total funding
Not listed
Headquarters
Boulder, CO
Founded
1972

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