Lead, Data AI & Engineering

Who we are: MHC is a global provider of AI-powered SaaS solutions for document, communication, and payment automation - purpose-built for highly regulated industries. We simplify complexity and unlock intelligence so organizations can deliver exceptional experiences with confidence. Our platform helps enterprise and mid-market organizations improve efficiency, ensure compliance, and modernize customer communications at scale. Customers use MHC solutions to generate more than 10 billion documents and process billions in AP payments annually. Recognized as a Leader in multiple G2 reports and featured in analyst reports from Gartner, IDC, Aspire, and Aragon, MHC is built for organizations that can't afford to get it wrong. People are at the center of everything we do - for our customers and within our own walls. MHC supports a flexible, work-where-you-live model, and for five consecutive years has been named one of Minnesota's Top Workplaces by the Star Tribune, based entirely on employee feedback. We are a team driven to grow, committed to being better than yesterday, and stronger together. We earn trust every day with our customers, our partners, and each other. We experiment boldly, and when our customers win, we win. For more information, visit mhcautomation.com. Who we are looking for: We're looking for a hands-on Lead, Data & AI Engineering to build the data layer for MHC and the intelligence on top of it. You will own how data is ingested, modeled, governed, and served across the company, and you'll partner with Product and Engineering to ship AI- and LLM-powered features into our product. This is a player-coach role. You will spend significant time in the code designing pipelines, building data models, and prototyping AI features while also managing and growing a small team of 1-2 data and AI engineers. You'll set the technical direction, establish the standards, and be accountable for both the platform and the people. Why join us? MHC is at a pivotal moment. With a strong foundation and bold growth ambitions, we're not just scaling, we're transforming. We're looking for someone who isn't here to maintain the status quo, but to define what data and AI can do for our business and our customers. This isn't a plug-and-play role. You'll have end-to-end ownership of green-field data and AI capability at a company with real data, real customers, and clear problems worth solving. You won't be handed a playbook you'll write it. You'll set the direction, build the foundation, and see your work shipped directly into the product, all while building and leading the team that does it. If you want to architect the future of a global SaaS company, not just join it this is your opportunity. What you will get to do: Build the data layer Architect. Design and build MHC 's core data platform — ingestion, transformation, storage, and serving layers — across batch and streaming workloads. Model. Model data for both analytics and product use cases, creating clean, well-documented, reusable datasets and a semantic layer the whole company can trust. Govern. Establish data quality, lineage, observability, and governance practices so data is reliable, discoverable, and secure. Pipe. Build the pipelines and feature/embedding stores that feed analytics, ML, and LLM applications. Create intelligence from data Mine. Turn raw operational and document data into intelligence — metrics, signals, predictions, and document understanding — that powers decisions and product features. Apply AI. Build and evaluate models and retrieval systems (including RAG over documents) that extract, classify, summarize, and reason over MHC 's data. Productize. Partner with Product to design and ship LLM-powered features — from prototype to production — with appropriate guardrails, evaluation, and cost controls. Lead the team Manage. Manage, mentor, and grow a team of 2–4 data and AI engineers; set goals, give feedback, and develop careers. Direct. Set technical standards and a pragmatic roadmap for data and AI; make build-vs-buy decisions and balance speed with long-term maintainability. Partner. Collaborate across Product, Engineering, and business stakeholders to align the data and AI roadmap with company priorities. Contribute. Stay hands-on — review code and designs, prototype hard problems, and set the bar for engineering quality. What Success Looks Like in This Role: First 90 days. In 90 days: you understand MHC 's data and systems, have a prioritized data &