How Engineers at McMaster-Carr Drive Real-World Impact Through Ownership
Kevin Matesi works as a senior software engineering manager at McMaster-Carr, an e-commerce company that supplies industrial products to plants around the world. While most of his day-to-day work revolves around computer systems, he said he sometimes tries to catch a glimpse of his team’s work in action on the warehouse floor.
“I find it inspiring to physically see how our systems that we build and support are powering our business day to day, and I’ve used these walks as an opportunity to clear my mind whenever I run into a challenging technical problem,” he said.
With support from leadership, Matesi said the engineering team is empowered to push the boundaries of what’s possible.
“In my experience, leaders at all levels of the company encourage us as engineers to challenge the status quo and are supportive of us prototyping our ideas to demonstrate potential benefits,” he said.
“In my experience, leaders at all levels of the company encourage us as engineers to challenge the status quo and are supportive of us prototyping our ideas to demonstrate potential benefits.”
How McMaster-Carr Uses AI and LLMs in Day-to-Day Engineering Work
Technologists at McMaster-Carr continuously seek new ways to move the needle on large-scale projects, and AI helps drive these efforts. Lead Engineer III Marissa Heffler and her teammates use LLM tools and other technologies to develop an internal, web-based repository that captures the company’s institutional memory of industrial sources and its product offering.
“As a department, we strive to adopt technologies that provide flexibility for individual projects and useful defaults for more standard activities,” she said.
To that end, Heffler frequently leverages LLM tools like Microsoft CoPilot to help convert logical descriptions into boilerplate queries, sort through dense vendor documentation, or code while ideating on proofs-of-concept. But no matter how her team leverages AI, Heffler said they treat the technology as a collaborator — not a replacement.
“Our developers are encouraged to find balance between using embedded AI tools to expedite the authoring of code or acceptance tests while maintaining a commitment to understanding the output and implications of any generated code,” she said.
Engineering Practices Heffler Champions on Her Team
- Making effective use of tech designs and pseudocode: “Throughout my career, I have learned the hard way the risks of diving head first into implementation. Especially when working with newer engineers or in business areas with less established systems, I believe taking the time to describe technical designs in plain English can pay dividends. In particular, I encourage a focus on describing core responsibilities like data contracts or logical units of work at this level, which are more difficult to unwind once they are baked into code.”
- Testing and recovery readiness: “This practice helps engineers develop a mindset of understanding their work in a broader context, helping them anticipate indirect implications of their work and grounding them in the impact of the larger system. Incorporating the practice of roll-back plans for riskier changes empowers engineers to move forward confidently, removing the stress of identifying a path to known good state in the heat of recovery.”
Lead Engineer II Claire Markey’s team supports the development of internal AI platforms that enable project teams and operational leaders to integrate AI into existing enterprise applications and create new tooling to automate operational workflows.
For Markey, the key to navigating the fast-changing AI landscape is knowing how to balance business needs with cutting-edge innovation.
“With AI, it’s easy to get caught up in what’s technically possible,” she said. “But the real value comes from understanding the specific problems teams are trying to solve and using that knowledge to build long-lasting, extensible systems that address those needs.”
About McMaster-Carr
Headquartered in Elmhurst, Illinois, McMaster-Carr is an e‑commerce company that distributes a broad range of products helping organizations maintain, repair, design, and build their industrial operations.
How Engineers Collaborate and Learn From Each Other at McMaster-Carr
For Matesi, every day brings a varied mix of technical problem‑solving, peer collaboration and opportunities to learn and lead.
He recalled a recent workday in which he was implementing an initial framework for a new application he was designing. After encountering a technical challenge, Matesi consulted a senior engineer who guided him through the issue. Later on, he had time to attend a tech talk about functional programming, have one-on-ones with engineers, and then align over future work with leadership.
“This is a fairly common occurrence for me and has been since I’ve joined the company,” he said. “Day to day, I can be as technical as I want to be while I’m leading a team, and I can easily collaborate with engineers to talk through challenging or interesting problems.”
“Day to day, I can be as technical as I want to be while I’m leading a team, and I can easily collaborate with engineers to talk through challenging or interesting problems.”
Quarterly planning sessions also help foster peer-to-peer-support, enabling team members to organize upcoming work and influence the direction of the team.
How Engineers Build and Learn Through Complex Systems at McMaster-Carr
Matesi said that these planning sessions have been especially beneficial for his team, as they focus on developing services for a new system that manages the routing of bins with customer orders to be packed, along with a new interactive packing experience designed to improve packer productivity and accuracy.
Throughout this project, he has used AI to generate code for unit tests and act as a training aid as he broadens his understanding of the mainframe programs that power McMaster-Carr’s warehouse operations.
“This has cut down a significant amount of time that I have previously spent writing boilerplate code to set up these types of tests,” he said. “This approach has also helped me accelerate basic bug busting to identify some potential edge cases where I have missed error handling.”
Matesi works across several programming languages and has learned that, with the right prompts, an LLM can quickly summarize what a program does once it understands his team’s paradigms.
“I have used this to accelerate my own learning by comparing the summary with my own interpretation to ensure that I am able to analyze the code correctly and to act as a tutor that I can pepper with questions as I learn how to modify the code to build new functionality,” Matesi said.
This has been extremely helpful to Matesi for learning a language that is not as well-supported or documented in the public community as languages like C# or Java.
As Matesi leads projects like this one, he often uses Docker Desktop for rapid prototyping, which allows him to quickly stand up isolated databases, such as SQL Server, Redis, or Kafka brokers — without dealing with the overhead of provisioning servers.
“This gives me a safe, isolated sandbox environment where I can experiment, and it has been extremely helpful from a learning perspective to get hands-on experience with various technologies,” he said.
At McMaster-Carr, engineers are encouraged to learn and adapt to new systems and technologies, honing their technical skills to grow into more well-rounded technologists.
“I’m becoming more comfortable with being uncomfortable and trusting my ability to learn the skills required and lean on engineers around me for support as I do so,” he said.
How Engineers Shape the Future — and Their Careers — at McMaster-Carr
Engineers at McMaster-Carr play a key role in identifying opportunities and shaping the direction of technical features.
“This occurs through direct collaboration with business stakeholders, involvement in feature planning discussions to provide technical input, opportunities to build broad domain knowledge across different business areas, and a deep understanding of how our systems are connected,” Markey said.
As her team continues to scale the company’s platform and add new features, Markey is looking for engineers who can balance technical depth with strong business judgement. Considering how quickly AI evolves, it’s critical for engineers to dig into the technical details while staying grounded in the company’s mission.
“An important part of this process is aligning cross-functionally with teams outside of the technology department to understand business requirements and translate between the technical possibilities and business needs,” Markey said.
Those who join her team will get to grow just as she has.
Markey recently led the company’s efforts to sign a new agreement with one of its commercial model providers that unlocked ten times the model capacity for key foundational models used by its internal enterprise systems, which she considers an important step toward scaling the company’s LLMs to support its 2026 ambitions.
Her team has also been working on an early prototype of a desktop application that allows employees to create and run their own AI agents that can connect to existing systems and use internal data to complete tasks and workflows autonomously.
“These capabilities enable subject-matter experts to design and build out their own process automations, while still ensuring enterprise-grade security, reliability and observability,” Markey said.
But one of the work experiences that excites her most is smaller in scale: It’s called “Implementation Spotlight,” and it’s an initiative where team members share an AI agent that operational leaders have built to solve a specific business challenge or automate a tedious workflow.
“Seeing the platform’s capabilities translate into these small but meaningful wins for different departments is very rewarding,” Markey said.
Frequently Asked Questions
What is it like to work on engineering teams at McMaster-Carr?
Engineers describe a culture of ownership and support where leaders encourage challenging the status quo, prototyping ideas and learning through hands-on problem-solving.
How does McMaster-Carr use AI and LLMs in engineering work?
Teams use LLM tools to support proofs-of-concept, convert logical descriptions into boilerplate queries or code, sort through vendor documentation and accelerate development — while treating AI as a collaborator rather than a replacement.
What kinds of projects do engineers work on at McMaster-Carr?
Projects include building warehouse and operational systems like services for routing bins with customer orders and a new interactive packing experience designed to improve productivity and accuracy.
How do engineers collaborate and learn from each other at McMaster-Carr?
Engineers collaborate through peer support (like talking through technical challenges with senior engineers), tech talks, one-on-ones and alignment with leadership, along with quarterly planning sessions that shape team direction.
What skills or qualities help engineers succeed at McMaster-Carr?
Engineers benefit from being adaptable and comfortable learning new systems and technologies, collaborating closely with peers and stakeholders, and balancing technical depth with strong business judgment as AI capabilities evolve.
