Who is Tom Smykowski, Your AI Product Engineer?
Tom Smykowski is a Poland-based, remote AI Product Engineer with nearly two decades of experience in product delivery, blending deep engineering, UX, and product thinking. He is the ideal hire for founders, CTOs, and executives seeking ownership from initial discovery through to production deployment, particularly for roles requiring the integration of AI into core product value. He specializes in building and modernizing systems, solving complex problems, and providing the technical leadership necessary to ship AI-driven products. His background as a Staff Software Engineer and founder ensures he understands both the strategic vision and the hands-on implementation required to succeed.
His approach is fundamentally product-minded. This means every technical decision, from selecting an LLM architecture to designing a user interface, is evaluated through the lens of user value and business outcomes. He doesn't just build AI features, he engineers AI products. This holistic skill set is proven across a diverse client portfolio including global names like DeLaval, Croissant, Ordnance Survey, Printify, GE Healthcare, and Unilever, as well as impactful work for institutions like the Silesian University of Technology and the Polish Tourism Organisation. For teams in the EU, UK, and US looking to leverage AI practically and effectively, Tom provides a rare combination of strategic insight and executional excellence.
Operating remotely from Poland, Tom is adept at collaborating across time zones with international teams, offering reliable overlap with US East Coast hours when needed. His engagement model is flexible, encompassing full-time employment, B2B contracts, and project-based consulting. Whether the need is for a founding engineer to build an AI-native MVP from scratch, a staff engineer to modernize an existing stack with AI capabilities, or a fractional technical leader to guide AI strategy, Tom's experience positions him to deliver immediate impact.
Defining the AI Product Engineer Role
An AI Product Engineer is more than a machine learning specialist or a traditional software developer. This role sits at the critical intersection of artificial intelligence, software engineering, and product management. The core responsibility is to translate business opportunities and user needs into functional, scalable, and maintainable AI-powered products. This requires a deep understanding of which AI techniques are appropriate, how to integrate them robustly into a full-stack application, and how to design the user experience around probabilistic, AI-driven outputs. It's a role that demands constant evaluation of trade-offs between model complexity, latency, cost, and ultimate user benefit.
In practice, an AI Product Engineer owns the entire lifecycle of AI features. This begins with discovery and prototyping, where they might rapidly test hypotheses using off-the-shelf APIs or open-source models. It extends to architecting the production system, which involves designing data pipelines, implementing retrieval-augmented generation (RAG) systems, building evaluation frameworks, and ensuring observability and monitoring are in place. They are responsible for the non-model code that makes AI reliable, which often constitutes the majority of the system. Their work ensures that AI is not just a demo, but a dependable, evolving component of the product.
For organizations, hiring an AI Product Engineer like Tom means bridging the common gap between data science research and product engineering. He brings the mindset to ask, "Should we build this?" alongside the skill to answer, "How do we build this right?" His experience in staff and principal engineering roles, such as at Croissant and as the founder of Websoul, has honed his ability to make architecture decisions that support both immediate AI integration and long-term product scalability. This end-to-end ownership is crucial for startups and established companies alike to move beyond AI experiments and achieve tangible product-market fit with intelligent features.
Core Technical Expertise and AI Stack
Tom's technical foundation is built on modern full-stack web development, which forms the essential substrate for any AI product. He has extensive, hands-on expertise with Vue.js, TypeScript, Supabase, and complex component libraries like AG Grid, demonstrated in large-scale projects such as leading the design system and rebrand for Printify ahead of its merger, a platform supporting over 10 million merchants. This deep frontend and backend experience ensures that AI integrations are seamless, performant, and deliver a polished user experience. His work is always grounded in principles of accessibility, clean APIs, and maintainable code.
On top of this strong engineering base, Tom specializes in AI-assisted workflows and AI-native software development lifecycles (SDLC). He advises on and implements AI Software Factories, incorporating agentic engineering, AI coding agents (like Claude Code, Cursor, and GitHub Copilot), and automated quality gates into development processes. This expertise isn't just about using tools, it's about systematically elevating team productivity and code quality through AI. He can conduct AI Software Factory setups, audits, and team workshops to transform how engineering teams build software, making them faster and more effective while maintaining high standards.
His AI product engineering work focuses on applied, practical integration. This includes designing and building systems that leverage large language models (LLMs) for content generation, classification, and conversational interfaces, computer vision for industrial applications as seen in his work with DeLaval and GE Healthcare, and predictive analytics for SaaS platforms like Websoul, which served over 32,000 businesses. He understands the infrastructure demands, from vector databases and embedding models to orchestration frameworks, ensuring the AI components are robust, cost-efficient, and scalable within the broader application architecture.
Product Thinking and Strategic Impact
The distinguishing factor of an AI Product Engineer is a relentless focus on outcomes. Tom's nearly twenty-year career is defined by shipping products that users love and that drive business growth. At Websoul, he founded and built a fintech SaaS marketing automation platform from the ground up, navigating product-market fit, scaling to thousands of customers, and managing the full technical stack. This founder's experience gives him an innate understanding of prioritization, resource constraints, and the importance of iterative learning, which he brings to every engagement, whether as a team member or a consultant.
This product thinking manifests in how he approaches AI projects. He starts with the problem and the user, not the technology. Before architecting a solution, he collaborates closely with founders, product managers, and designers to define success metrics, identify risks, and validate assumptions. His work with clients like the Marshal Office of the Silesian Voivodeship and the Institute of National Remembrance involved turning complex public-sector requirements into intuitive, user-focused digital products, a skill directly transferable to making complex AI systems accessible and valuable to end-users.
For leadership teams, Tom acts as a force multiplier. He can serve as a fractional CTO or technical advisor, providing AI strategy and product roadmapping guidance. He is skilled in technical due diligence, architecture reviews, and code audits, offering an expert assessment of a team's readiness for AI integration or the health of an existing codebase. His ability to communicate complex technical concepts clearly makes him effective in executive briefings for CEOs and CTOs, as well as in corporate training sessions aimed at upskilling entire engineering teams in AI adoption and modern development practices.
Collaboration and Remote Work Model
Tom has perfected the art of remote, asynchronous collaboration over years of working with distributed teams across continents. Based in Poland, he seamlessly integrates with teams in the EU, UK, and North America. He is proactive in establishing clear communication rhythms, documentation practices, and knowledge-sharing protocols that keep projects moving forward smoothly across time zones. His experience includes successful collaborations with US-based teams at Croissant and Printify, demonstrating his ability to maintain productivity and alignment despite geographical distance.
His work style is built on transparency and proactive contribution. He thrives in environments that value ownership and trust, where he can take a problem and run with it from conception to delivery. He is equally comfortable leading technical initiatives, as he did as the lead frontend engineer at Fream on industrial SaaS, or working as a collaborative senior contributor within a larger engineering organization. He values in-person connection for key moments and is available for occasional on-site workshops, client visits, and team offsites to build relationships and drive intensive planning sessions.
Tom is also a committed advocate for knowledge sharing and team growth. He has a background in technical writing, public speaking, and conference presentations. This translates into his daily work through clear documentation, mentoring of junior engineers, and facilitating workshops. When he joins a team, he elevates not only the codebase but also the collective skill level and communication standards of the group, fostering a culture of continuous learning and excellence, which is particularly valuable during the rapid evolution of AI tools and techniques.
When Hiring Tom as Your AI Product Engineer is a Good Fit
Engaging Tom Smykowski as your AI Product Engineer is an ideal strategic move if you are a founder, CTO, or product leader who needs more than just coding skills. He is the right fit when you require someone to own the entire journey of an AI-powered feature or product, from validating the initial concept and designing the system architecture to leading the implementation and ensuring its successful launch and iteration. His blend of staff-level engineering prowess, founder-level product intuition, and practical AI integration experience is uniquely valuable for organizations that want to move decisively in the AI space without the overhead of large consulting firms.
Consider reaching out if your situation involves building a new AI-native SaaS product or startup and you need a founding or principal engineer to establish the technical vision and execute it. He is equally suited for established companies, like those in his client portfolio, that are modernizing an existing platform and need to thoughtfully integrate AI capabilities without disrupting core business functions. If you are looking for a fractional technical leader to audit your current stack, advise on AI strategy, or upskill your team through corporate training and workshops, his consulting services provide targeted, high-impact expertise.
Ultimately, if you value deep ownership, clear communication, and a partnership approach to building great products, Tom's remote, collaborative model will align with your goals. He is committed to being a long-term asset to your team, whether on a full-time, part-time, or project basis, helping you navigate the complexities of AI product development to achieve tangible business results.