At Thoughtful AI, our Customer Engineers are the linchpin in delivering transformative AI solutions that revolutionize healthcare operations. This unique position was created to bridge the gap between complex technical implementations and customer needs, ensuring seamless integration and maximum impact. Today, we dive into the professional life of Danny Mathieson, one of our talented Customer Engineers, to explore how he leverages his engineering expertise to solve complex problems and drive value for our customers.

The Genesis of the Customer Engineer Role

The inception of the Customer Engineer role at Thoughtful AI arose from a critical need identified by Chris Williams, the SVP of Customer Engineering, Security, and Support. Chris provides insight into this evolution.

"We initially thought a project manager could manage the technical people," Chris explains. "However, we quickly realized that we needed someone who could understand both the technical and business aspects of our projects. The traditional approach was like a game of telephone—customers would communicate issues to project managers, who would then relay these messages to engineers, and back to the customers, often resulting in miscommunication and delays."

The solution was to hire individuals with engineering backgrounds who could directly interact with customers, effectively eliminating the middleman. "By having Customer Engineers who can talk to customers and understand their AI development needs, we build trust and deliver solutions more efficiently," Chris adds.

Bridging the Gap Between Technology and Business

Danny's role as a Customer Engineer exemplifies the blend of technical expertise and customer interaction that Thoughtful AI envisioned.

"My data background helped in designing processes that engineers implement," Danny explains. "When issues arise, I can trace them back through the design and code, effectively communicating with both the customer and engineers. This ensures that problems are addressed accurately and efficiently."

"One of the core aspects of my job is to serve two key stakeholders: the customer and the engineers," Danny continues. "I need to make sure we're building systems that meet customer specifications while also ensuring that the engineering team understands the necessary steps to implement these solutions."

A Day in the Life: Solving Problems and Driving Value

Morning: Proactive Problem-Solving

Danny's day begins with a proactive approach to problem-solving. "Every morning, I review the performance of our AI Agents from the previous night," he says. "This includes checking for any issues and addressing customer feedback." This process ensures that the AI solutions are functioning as intended and any anomalies are promptly fixed.

Midday: Customer Engagement and Collaboration

One of the most significant aspects of Danny's role is direct engagement with customers. Working closely with customers allows him to understand their challenges and provide tailored solutions. "When customers realize that the person they're talking to not only understands their business problem but can also dive into the technical details, it’s a game changer," Chris highlights. "They feel heard and supported, and it builds tremendous trust and progress."

Danny works closely with the internal engineering team to tailor AI solutions to specific needs. "Our customers often have very particular RCM requirements, and it’s my job to translate these into technical specifications that our engineers can work with," Danny says. This involves consistent communication with the customers whether it’s on Teams, Slack, Text, or meetings.

"Listening is a critical part of the job," Danny notes. "Many of our customers are new to advanced technology, so it's important to understand their concerns and explain our solutions in a way that makes sense to them."

"We're going outside of the box by implementing AI, but also need to stick to their processes and respect their flows. Their processes are a sensitive area so if we do go out of the box, we make sure we explain the changes in a way that the customers can understand so we're not shaking their whole world view on their process."

"Today, we worked on building an eligibility verification workflow for a customer. They needed to automate the verification of insurance details whenever a patient makes an appointment. The process involves navigating various insurance portals, each with different layouts and data structures. We created a feedback loop between the customer and our engineering team to quickly address and fix any issues that arise."

Other days, Danny is knee-deep in mapping out a Master Automation Plan (MAP). It's a central skill of the Customer Engineer, building and maintaining this detailed document that outlines the AI agent's tasks in both business and technical terms. It includes edge cases, dead ends, happy paths, and process flows. This plan serves as a contract with the customer and a guide for engineers. It's a product requirements document that is human-readable but also serves as a technical document.

Some days, Danny is navigating technical challenges. "One challenge was dealing with unstructured data, like ambiguous paragraphs in dental insurance policies," Danny says. "Initially, our AI agents struggled with this, sending numerous unresolved issues back to the customer. After dissecting the problem, we opted for a large language model (LLM) to extract key data points from these paragraphs. Over time, by showing the model examples and refining it with customer feedback, it became more accurate, turning a negative situation into a valuable feature."

By putting a Customer Engineer in a forward-deployed sense, where they're actually working directly with the customer on their problem, they become like a Swiss army knife of technology solutions, Williams notes.

Afternoon: Quality Assurance and Client Engagement

Quality assurance is non-negotiable. “I spend a significant portion of my afternoon conducting or guiding engineers through rigorous tests on new deployments,” Danny explains. “This involves running simulations, analyzing results, and making necessary adjustments. Ensuring our AI agents perform flawlessly in real-world scenarios is critical to maintaining our reputation for reliability and trust.”

Analyzing performance data helps identify patterns and areas for improvement. The AI compiles reports that highlight the effectiveness of our AI solutions, offering actionable insights to our clients. “Today, I'm preparing a report for a CFO of a large healthcare network, demonstrating how EVA has significantly reduced claim denials and improved revenue flow,” Danny shares.

Before wrapping up, Danny revisits client feedback and prepares for tomorrow's engagements. “Ensuring that our clients feel heard and valued is paramount. I jot down key points from today's interactions and plan follow-up actions to address any concerns or suggestions.”

Danny also appreciates the variety his role provides. "Each project feels like my own little company," he shares. "I get to sit down with a blank canvas and figure out the best way to solve a problem. The support system around me is geared towards identifying and solving customer issues quickly. It’s rewarding to start at 8 a.m. and look up at 6 p.m. realizing how much we've accomplished."

The Most Rewarding Parts of the Job

For the Customer Engineering team, the most fulfilling aspect of the role is the tangible impact on the healthcare system. "What we’re doing is really important," Danny says. "It’s detailed work, but these AI agents we build can be used for years. Optimizing the entire revenue cycle management (RCM) process, making it more efficient, is incredibly rewarding."

The AI agents don't just replicate human processes—their capabilities extend far beyond that of a human. By training AI agents to collect and report data, customers are empowered with information they previously couldn’t access. "Our customers often struggle to get a full bird’s-eye view of their data. They might know a patient was seen and what they got paid, but they don’t have insights into the entire RCM cycle," Danny explains.

Chris adds, "Our customers benefit greatly from seeing their revenue, costs, financial allocations, and expenditures all on one dashboard or report. They want to know where their money is going and how to use that data to make decisions."

The real "aha" moment, Danny notes, comes when customers see detailed reports of what the AI agent did. "It’s shocking for them to see how much output the agent produces and how much better the results are. We roll out their analytics, and they say, 'Oh my God, you did that 15,000 times in five days?!' They see step-by-step what was accomplished, exactly why and where they failed, who we skipped, and what portal it went to—all of that, which no human employee could track so meticulously. This gives them the ability to understand where processes fail and how they can improve. And from their side, it seems just as easy as flipping a switch."

Differentiating from Solution Architects

Customer Engineers at Thoughtful AI differ significantly from solution architects. While solution architects operate at a 30,000-foot view, Customer Engineers can dive deep into the technical details. Chris explains, "Solution architects are up there navigating the broader vision, managing teams, and setting up calls. They often come from backgrounds where they managed projects and teams but were not hands-on."

Chris continues, "A solution architect might say, 'We need more user accounts to log in and run more processes.' They can identify the need, but can they request the accounts, work with engineers to parallelize the effort, and get it up and running? That's where Customer Engineers shine. They connect the business outcome to the technical requirements and execute them hands-on."

This hands-on approach allows Customer Engineers to directly address issues, work on code, and ensure that solutions are implemented effectively. "We don't just create a plan and hand it off; we dive into the actual code and work closely with the engineering team to make it happen," Chris emphasizes.

Qualities of an Ideal Candidate

The ideal candidate for the Customer Engineer role at Thoughtful AI has a strong problem-solving mindset, adaptability, and a customer-focused approach. They must be proactive, comfortable with ambiguity, and technically competent.

• Problem-Solving Mindset: "You need to be able to break a complex problem down into simple tasks and then explain those simple tasks to someone," Danny emphasizes.
• Adaptability and Flexibility: "Be ready for anything. You get new things thrown at you every single day in this job. Staying on your toes and being malleable while also making sure you can provide value is crucial," Danny notes.
• Customer-Focused: "You need to meet the customer where they're at and listen more than anything," Danny explains.
• Comfort with Ambiguity: "If you like diving into unforeseen problems headfirst, it's probably a good fit. Embrace the ambiguity and be ready to tackle a variety of challenges," Danny advises.
• Technical Competence: "You need to be able to read code to work with the engineers and customers," Danny explains.
• Resilience and Persistence: "One of my favorite parts of the job is when everything seems to be falling apart. Nothing is going right, but I get to dive deep and find a solution," Danny says.

Looking Ahead

The role of a Customer Engineer at Thoughtful AI is not just about solving technical problems; it’s about bridging the gap between technology and practical application. Danny's journey highlights the importance of this role in transforming healthcare through AI.

"There's no better type of role to truly understand what the next wave of technology is going to look like. Most people agree that AI is transformative, but unless you're on the ground, you're not fully going to understand what AI is going to change. In this role, we're so hands-on in using AI, determining where to use and integrate LLMs, OCR, and using and coding AI (with RAG for example) to build and solve real problems and drive value in ways that I think a lot of people are missing the mark. Being in this role is a great way to have a good idea of where the puck is going in the next few years."

If you're passionate about leveraging your engineering skills to drive innovation in healthcare, explore career opportunities at Thoughtful AI here. Join us in revolutionizing healthcare with AI. 🚀