Tom Smykowski is a product-minded staff software engineer with nearly two decades of experience in product delivery, specializing in SaaS scaling architecture for founders, CTOs, and executives. He is the ideal hire for teams needing ownership from discovery through production, combining hands-on engineering with deep architectural thinking to build scalable, maintainable systems. Based in Poland, he works remotely with EU, UK, and US teams, bringing proven experience from scaling platforms serving millions of users.
Understanding SaaS Scaling Challenges
Scaling a SaaS product presents unique architectural challenges that differ from traditional software. It's not merely about handling more users, but about evolving a system under constant change, where feature velocity, data integrity, and performance must be balanced. A successful scaling strategy anticipates bottlenecks in database queries, API response times, deployment pipelines, and third-party service integrations before they impact the user experience.
Many SaaS companies reach a critical juncture where their initial, rapid-growth architecture begins to creak under load. This often manifests as slow page loads for certain user segments, deployment times stretching into hours, or difficulty in onboarding new engineering talent due to a convoluted codebase. Addressing these issues requires a holistic view that considers not just the technology stack, but also team structure, development workflows, and cost efficiency. An engineer specializing in scaling architecture brings this systems-thinking approach to ensure growth is sustainable.
The goal of effective SaaS scaling is to build a platform that is resilient, cost-effective, and enables rapid iteration. This involves decisions around microservices versus modular monoliths, database sharding strategies, caching layers, and asynchronous job processing. It also encompasses the developer experience, ensuring that the architecture supports a growing team with clear boundaries, comprehensive testing, and efficient CI/CD pipelines. Getting this foundation right is what separates SaaS products that plateau from those that can scale to serve tens of millions of users.
Proven Experience with High-Growth Platforms
Tom's hands-on experience with scaling is drawn from pivotal roles at high-growth companies. At Printify, he contributed to the design system and rebranding initiative ahead of a significant merger, working within a frontend engineering organization of around 60 engineers serving a platform of over 10 million merchants. This context required architectural decisions that supported a large, distributed team working on a unified product experience, a classic SaaS scaling challenge.
Previously, as a Staff Software Engineer at the workplace platform Croissant, he worked in a direct partnership with the CEO and CTO. This role involved deep dives into compliance and collaboration features, where architectural choices directly impacted product viability and user trust. Building features that scale involves more than just code, it requires understanding business constraints and regulatory requirements, which are integral to sustainable SaaS growth.
His foundational experience comes from founding Websoul, a marketing automation SaaS that served over 32,000 businesses. As the builder of a product from scratch, he navigated the entire lifecycle from MVP to scaling, dealing with fintech integrations, complex data grids using AG Grid, and backend architecture with Supabase. This founder-level perspective is invaluable for SaaS scaling, as it aligns technical decisions tightly with business outcomes and user acquisition.
Architectural Patterns for Scalable SaaS
A key principle in SaaS scaling architecture is designing for change. This often leads to adopting a modular monolith or microservices approach, depending on team size and product maturity. A modular monolith, especially using tools like Nx for Angular or React, can provide excellent developer experience and deployment simplicity for mid-stage SaaS products, allowing for clear domain boundaries without the operational overhead of distributed systems.
Data architecture is another critical pillar. As user bases grow, database strategies must evolve from a single PostgreSQL instance to include read replicas, connection pooling, and eventually strategic sharding or moving to managed services. Caching strategies using Redis or CDN configurations become essential to offload repetitive queries and serve static assets efficiently. Tom's work with platforms handling significant traffic informs practical, incremental approaches to these complex problems.
Finally, the frontend architecture must scale alongside the backend. This involves establishing robust design systems, as Tom did at Printify and Fream, to ensure UI consistency and development speed across large engineering teams. It also means implementing advanced state management, lazy loading, and performance monitoring to keep the user interface fast and responsive. A scalable frontend is not an afterthought, it is a core component of user retention and satisfaction in a competitive SaaS market.
Integrating AI and Automation into Scaling
Modern SaaS scaling increasingly leverages AI and automation to boost developer productivity and system intelligence. Incorporating AI coding agents, automated testing suites, and AI-assisted quality gates can dramatically accelerate development cycles and reduce bugs in production. This shift towards an AI-native software development lifecycle (SDLC) is a strategic advantage for scaling teams.
Tom offers specific expertise in setting up what he terms 'AI Software Factories'. This involves integrating tools like Claude Code, Cursor, or GitHub Copilot into team workflows, establishing patterns for AI-generated code review, and automating repetitive tasks. For a scaling SaaS company, this translates to higher feature output without a linear increase in engineering headcount, a crucial efficiency gain.
Beyond development, AI can be woven into the product itself to provide scalable, intelligent features. Whether it's implementing smart search, predictive analytics, or personalized user experiences, AI integration must be architected for scalability from the start. This means considering model training pipelines, inference API design, and cost management for AI services. An engineer with AI product experience can ensure these features enhance the product without becoming a reliability or cost burden.
The Remote Collaboration Advantage for Scaling
Scaling a SaaS product often requires tapping into global talent pools. Tom's remote work model, based in Poland with collaboration across EU, UK, and US time zones, exemplifies this modern approach. Effective remote collaboration is itself an architectural concern, requiring clear documentation, asynchronous communication protocols, and tooling that supports a distributed team.
For SaaS companies scaling with remote or hybrid teams, having a lead engineer who is adept at this model is invaluable. It ensures architectural decisions are communicated clearly, knowledge is shared effectively, and the development process remains smooth despite geographical dispersion. Tom's experience includes occasional on-site workshops and client visits, providing the necessary human connection while maintaining the flexibility of a remote-first structure.
This model aligns perfectly with the needs of scaling startups and established companies alike. It allows access to senior-level, staff engineering expertise without the constraints of a local hiring market. For US-based teams, the overlap with US East Coast hours facilitates real-time collaboration when needed, while the asynchronous work cadence promotes deep focus work on complex architectural problems.
When This is a Good Fit
Hiring Tom for your SaaS scaling architecture needs is a strong fit if you are a founder, CTO, or technical lead of a growing SaaS product facing scalability challenges. It is ideal if you need an engineer who can take ownership from architectural design through to production implementation, who understands the business implications of technical decisions, and who has a proven track record with platforms serving millions of users. His remote, Poland-based model is perfect for international teams in the EU, UK, and US seeking senior-level expertise to build a foundation for sustainable growth.