Who is the AI Engineer for Hire?
Tom Smykowski is a senior AI engineer for hire, a product-minded technical leader with nearly two decades of experience in software delivery. He specializes in building and integrating artificial intelligence solutions, from initial discovery through to production deployment, for founders, CTOs, and executives. His work combines hands-on engineering with strategic product thinking, making him an ideal hire for teams needing ownership over complex AI initiatives, whether for new product development, system modernization, or scaling SaaS platforms.
Based in Poland, Tom works remotely with international teams across the EU, the UK, and the US, including East Coast time-zone overlap. His background spans staff and senior engineering roles, founding a SaaS business, and delivering projects for marquee clients like Croissant, Printify, and GE Healthcare. This blend of deep technical skill, business acumen, and remote collaboration expertise positions him as a strategic asset for organizations looking to leverage AI effectively.
His approach is fundamentally product-led. He focuses on solving real business problems with AI, ensuring that technical implementations drive user value and commercial outcomes. Whether the goal is to build an AI-native application from scratch, modernize an existing system with intelligent features, or establish an AI software factory for developer productivity, he provides the full-stack engineering and leadership necessary to succeed.
AI Engineering Expertise and Project Experience
Tom's AI engineering expertise is built on a foundation of full-stack software development and product leadership. His project portfolio demonstrates a consistent ability to tackle complex, high-stakes challenges. For instance, as a Staff Software Engineer at Croissant, a workplace platform, he worked in close partnership with the CEO and CTO on compliance and collaboration features, a role requiring meticulous technical execution and strategic product alignment. This experience in a scaling startup environment is directly applicable to AI projects, where balancing innovation with robustness is critical.
At Printify, a platform serving over 10 million merchants, he led frontend efforts on a major design system and rebrand ahead of a strategic merger. Managing a frontend engineering cohort of around 60 developers required architectural foresight and systematic execution. For AI initiatives, this translates to an understanding of how to build scalable, maintainable systems that large engineering teams can work on effectively, a crucial consideration when deploying AI models and pipelines at scale.
Earlier, as the founder of Websoul, he built a marketing automation SaaS used by over 32,000 businesses, incorporating fintech elements. This venture required end-to-end ownership, from product vision and architecture using Vue, TypeScript, and Supabase, to growth and operations. This founder-level perspective is invaluable for AI projects, as it ensures engineering decisions are always made with the product, the user, and the business model in mind, avoiding the common pitfall of technology for its own sake.
Technical Stack and AI-Native Development
Tom's technical proficiency provides a robust platform for AI engineering. His core stack includes modern frontend and full-stack technologies like Vue.js, TypeScript, Supabase, and AG Grid, complemented by deep experience in design systems, accessibility, and API development. This full-spectrum capability is essential for AI product engineering, as successful AI features are rarely just models in isolation, they are integrated components within larger, user-facing applications.
He actively employs and advises on AI-assisted engineering workflows, including the setup and optimization of AI software factories. This involves implementing agentic engineering practices, leveraging tools like Claude Code, Cursor, and GitHub Copilot, and establishing AI-native software development lifecycles (SDLC) with integrated testing and quality gates. For teams looking to boost developer productivity and accelerate delivery, his consulting can transform how engineering work is done.
His work spans mobile and web platforms, ensuring AI solutions are deliverable across the digital touchpoints that matter to users. Whether building a new AI-powered SaaS application, integrating large language models (LLMs) into an existing enterprise platform, or creating data-intensive interfaces with AG Grid for AI insights, he has the technical breadth to execute. This stack, combined with a focus on maintainable and scalable code, ensures AI integrations are sustainable long-term investments.
Industries and Client Collaboration
Tom has delivered software solutions across a diverse range of industries, providing him with the contextual understanding needed to apply AI effectively. His client list includes global names in agri-tech (DeLaval, Bunge), industrial mapping (Ordnance Survey), print-on-demand e-commerce (Printify), healthcare (GE Healthcare), consumer goods (Unilever), and public sector institutions like the Polish Tourism Organisation and the Marshal Office of the Silesian Voivodeship. This variety means he can quickly grasp domain-specific challenges and opportunities.
In the industrial and B2B SaaS space, such as his work with Fream on industrial SaaS and design systems, he focused on conversion-driven UX and complex data visualization. AI applications in these sectors might involve predictive maintenance, supply chain optimization, or intelligent data analysis tools. His experience building for specialized, high-stakes environments ensures that AI solutions are not only technically sound but also usable and valuable for expert users.
His collaboration style is geared towards founders, product managers, designers, and engineering teams. He excels at translating complex requirements from diverse stakeholders into clear technical plans and user-focused products. For AI projects, which often involve uncertain requirements and exploratory phases, this ability to communicate effectively, manage expectations, and iterate based on feedback is as important as the coding itself. He is adept at both async communication for distributed teams and in-person collaboration for workshops and offsites.
AI Consulting, Training, and Leadership Engagements
Beyond hands-on engineering, Tom offers targeted AI consulting and training services designed to uplift entire teams and organizations. This includes AI Software Factory consultations and setup, helping engineering departments integrate AI agents and tools into their daily workflows to dramatically improve productivity and code quality. For leadership, he provides CEO and CTO AI briefings, offering strategic overviews of the landscape, risks, and opportunities.
He conducts corporate AI training and engineering workshops, ranging from executive briefings to deep-dive technical sessions for development teams on AI coding, testing, and SDLC integration. These sessions are practical and aimed at immediate upskilling. His background in technical writing, book authorship, and public speaking ensures complex concepts are communicated clearly and effectively, maximizing the return on training investment.
For organizations needing ongoing strategic direction, he is available for fractional CTO and technical advisory engagements, focusing on AI strategy, MVP architecture for AI products, and overall technical leadership. These services are particularly valuable for startups and scale-ups that need experienced guidance without the full-time executive overhead. All consulting and training is offered remotely worldwide, with occasional on-site workshops available for key planning sessions or team launches.
When This is a Good Fit
Engaging Tom as your AI engineer is an excellent fit if you are a founder, CTO, or technical leader seeking a senior-level partner to own and drive AI initiatives from concept to production. It is ideal for teams building new AI-powered products, needing to integrate LLMs or machine learning into existing platforms, or aiming to establish modern, AI-assisted engineering practices. If you value a combination of deep hands-on coding skill, product strategy, and the ability to communicate complex ideas to both technical and non-technical stakeholders, this collaboration will deliver significant value. He integrates seamlessly into remote or hybrid teams across Europe, the UK, and North America.