Who is an Applied AI Engineer and Why Hire Tom?
Tom Smykowski is an applied AI engineer and product-minded technical leader with nearly two decades of experience in software delivery. He is the ideal hire for founders, CTOs, and executives seeking ownership from discovery through production, particularly for roles that combine hands-on engineering, product strategy, and AI-native development. His background spans staff and senior engineering positions, founding a SaaS business, and delivering complex projects for organizations like Croissant, Printify, and GE Healthcare, making him uniquely positioned to translate AI potential into tangible product outcomes.
An applied AI engineer focuses on integrating artificial intelligence technologies into real-world products and systems to solve specific business problems, rather than purely researching new algorithms. This role requires a blend of software engineering rigor, product sense, and an understanding of AI/ML capabilities to build scalable, maintainable, and user-centric solutions. Tom embodies this blend, having built products from scratch and modernized legacy systems across industries, always with an eye on practical delivery and measurable impact.
His approach is particularly valuable for teams looking to adopt AI without sacrificing engineering best practices. He works remotely from Poland, collaborating effectively with international teams across EU, UK, and US time zones, including US East Coast overlap for synchronous collaboration when needed. This global flexibility allows him to integrate seamlessly with distributed teams while bringing a deep, product-focused engineering perspective to applied AI challenges.
Bridging AI Engineering with Product and UX Thinking
The most effective applied AI engineers do not operate in a technical vacuum. They understand that the success of an AI feature is measured by user adoption, business value, and integration into the broader product ecosystem. Tom's career is defined by this product and UX thinking, evidenced by his work on design systems, conversion-focused UX, and compliance-driven features. At Croissant, as a Staff Software Engineer, he partnered directly with the CEO and CTO on compliance and collaboration tools, ensuring technical decisions supported product goals.
This product mindset is critical when deploying AI. It ensures that AI capabilities, such as predictive features, personalization, or automation, are designed with the end-user in mind and are built into a coherent, accessible user experience. His work on the Printify design system ahead of its merger with Printful, scaling for over 10 million merchants and approximately 60 frontend engineers, demonstrates his ability to architect systems that enable rapid, consistent product development, a principle that directly applies to building scalable AI-powered product interfaces.
Furthermore, his experience as the founder of Websoul, where he built a marketing automation platform serving over 32,000 businesses, required him to wear every hat from product manager to lead engineer. This firsthand experience in taking a product from zero to scale provides him with an innate understanding of the trade-offs, priorities, and iterative processes necessary to successfully apply AI within a product roadmap, ensuring that AI initiatives are aligned with business growth and user needs.
Technical Foundation and AI-Native Development
Tom's applied AI engineering is built upon a robust full-stack technical foundation. His expertise includes modern JavaScript frameworks like Vue.js and React, TypeScript for type-safe development, backend technologies like Supabase, and complex UI components with AG Grid. This comprehensive skill set allows him to build the entire pipeline required for AI applications, from the data layer and APIs to the interactive frontend interfaces that present AI-driven insights to users.
In the context of AI, this translates to building what he terms "AI Software Factories." This involves setting up agentic engineering workflows, integrating AI coding agents like Claude Code or Cursor, and establishing an AI-native Software Development Lifecycle (SDLC) with appropriate quality gates and automation. He helps teams adopt these tools not just for novelty, but to tangibly improve developer productivity (DevEx), CI/CD pipelines, and test automation, thereby accelerating the entire product delivery cycle.
His consulting offerings, such as AI Software Factory Setup and AI Team Workshops, are direct extensions of this hands-on expertise. He focuses on practical adoption, helping engineering teams upskill and integrate AI tools into their daily workflows to build better software faster. This technical pragmatism ensures that the "applied" in applied AI engineering results in concrete improvements in code quality, system architecture, and team output, not just theoretical experimentation.
Proven Delivery Across Industries and Scale
Credibility in applied AI comes from a history of delivering complex software systems under real-world constraints. Tom's portfolio includes enterprise-level projects for global brands and scalable SaaS products. He has worked with GE Healthcare and Unilever on industrial applications, contributed to geospatial systems for Ordnance Survey, and developed fintech SaaS at Websoul. This diversity proves his ability to understand domain-specific problems, which is the first step in effectively applying AI, as the technology must be tailored to the unique data and processes of each industry.
At Printify, his work on the design system and rebrand was a strategic project that supported the platform's massive scale and eventual merger. Similarly, his staff engineering role at Croissant involved navigating the complexities of workplace platform compliance. These experiences honed his skills in building maintainable, scalable systems, which is non-negotiable when deploying AI models that may require significant computational resources, data pipelines, and iterative model updates in a production environment.
His earlier work in industrial ERP with Insoft Serwis and technical writing for Webhosting.pl further underscores a career-long commitment to clear communication and solving tangible business problems through technology. Whether the client is a government body like the Institute of National Remembrance, a university, or a high-growth startup, Tom's methodology remains consistent, understand the core problem, architect a robust solution, and execute with ownership through to production and beyond.
Collaborative and Strategic Engagement Models
Tom operates as a remote contractor and consultant, offering flexible engagement models tailored to project needs. He is available for full-time and part-time B2B contracts, project-based consulting, fractional technical leadership, and corporate training. This flexibility makes him an ideal partner for startups seeking founding-level AI engineering expertise, scale-ups needing to modernize systems with AI, or larger enterprises looking to upskill their teams and audit their AI adoption strategies.
His communication style emphasizes knowledge sharing. As a technical writer, book author, and public speaker, he excels at translating complex AI and engineering concepts for diverse audiences, from engineering teams to CEOs and founders. This is reflected in his service offerings, which include CEO/CTO AI Briefings, Corporate AI Training, and Engineering Webinars. He believes that successful AI adoption requires alignment across the organization, and he facilitates this through clear, strategic communication.
Based in Poland, he is adept at asynchronous communication and cross-time-zone collaboration, making him a seamless fit for remote-first and distributed teams in the EU, UK, and North America. He is also available for occasional on-site workshops, client visits, and team offsites to foster deeper collaboration when required. This blend of remote efficiency and strategic in-person engagement provides teams with senior-level AI engineering insight without the overhead of a traditional enterprise consultancy.
When Hiring This Applied AI Engineer is a Good Fit
Engaging Tom as your applied AI engineer is an excellent strategic move if you are a founder, CTO, or product leader who needs more than just an AI researcher or a generic software developer. The ideal scenario is when you require a product-minded technical owner who can architect and build AI-infused features, modernize your existing stack to be AI-ready, and provide leadership to upskill your team. If your goal is to move from AI experimentation to robust, scalable product integration with a focus on user experience and business outcomes, his blend of engineering depth, product strategy, and practical AI application will deliver significant value.