Development
ActiveCampaign is seeking a Software Engineer to join our Kraków Hub and build production-ready AI agents for autonomous marketing. Our platform empowers businesses to automate their customer engagement — and we are now extending that with intelligent, agentic workflows that can reason, act, and adapt on behalf of our customers. Our first wave of agents is already in production. This role will drive the expansion, building the next generation of autonomous experiences across the full breadth of the platform.
You 'll work at the intersection of solid software engineering and applied AI — designing, building, evaluating, and operating agents that run at scale in a production marketing automation platform. This means engineering rigor comes first: agents need to be reliable, observable, performant, and safe before they are clever.
Our Kraków Hub houses multiple engineering teams — Forms, Integrations, Ecommerce, Agency, CRM, Mobile, CampaignsUI, and Content — working across different product pillars with a shared focus on building agentic workflows into all core functionalities across the platform. You will collaborate closely with these teams, understanding their domains and building agents that integrate seamlessly into the broader system.
This is not a pure research or ML role. We need engineers who can build — end to end — from prompt design through backend orchestration to frontend integration, and who can ship, measure, and iterate fast. Our environment moves quickly — we value high ownership, tight feedback loops, and close cross-functional collaboration. If you thrive in a hands-on, high-pace setting where you build, ship, and iterate rapidly, this role is for you.
What your day could consist of:
- Designing and building production-grade AI agents and autonomous marketing workflows across the ActiveCampaign platform
- Implementing multi-step agentic flows involving LLM orchestration, tool use, and integration with platform services
- Working with LLM APIs (prompt engineering, response handling, evaluation) and building reliable, testable agent pipelines
- Designing and running agent evaluations — building eval frameworks, defining quality metrics, and continuously measuring agent accuracy, reliability, and performance in production at scale
- Monitoring and optimizing agent performance — latency, cost, token usage, error rates — and iterating rapidly based on production dataIterating on agent behavior based on user feedback, observability data, and quality metrics
- Leveraging AI-assisted development tools and practices in your daily workflow — you don't just build AI features, you build with AI
- Writing production-quality code in Python for agent services and backend orchestration
- Contributing to PHP backend and frontend (React/Ember) integration points where agents interact with the core platform
- Building and maintaining APIs, data flows, and service interfaces that agents depend on
- Working iteratively — shipping code fast, learning from production, and improving continuously
- Ensuring code quality through testing, code review, and adherence to engineering standards
- Participating in on-call rotation for incidents related to agent services
- Working closely with Product, Design, and domain engineering teams to define agent capabilities and user experiences
- Engaging in pairing and code reviews across teams
- Contributing to documentation of agent architectures, patterns, and best practices
- Maintaining regular overlap with US-based teams (Chicago timezone) to ensure alignment and tight collaboration across the organization