Principal AI Engineer - Poland

AI-Powered Software Platform Engineer

Required

Skills & Experience:

• Strong software engineering experience building production-grade backend systems, APIs, workflow engines, developer platforms, internal tools, or distributed systems.
• Experience building tools or platforms that improve engineering productivity, software delivery, operational awareness, or developer workflows.
• Experience building or integrating AI-powered systems, including LLM-enabled applications, agentic workflows, retrieval-based architectures, tool-use patterns, or AI-assisted automation.
• Understanding of emerging agentic software delivery patterns, including graph-based workflows, coding agents, and AI-assisted engineering approaches.
• Experience designing reusable platform capabilities, shared abstractions, and scalable engineering solutions.
• Strong understanding of workflow orchestration, state management, execution patterns, validation, retries, branching logic, and human approval processes.
• Experience building systems with reliability, observability, security, scalability, maintainability, and operational excellence as core design principles.
• Strong collaboration and communication skills with the ability to work across multiple engineering disciplines.

Job Description:

A global fitness technology company is building AI-powered platforms that help engineering teams build, ship, understand, and operate software more effectively. Day to day:
This person will design, build, and evolve internal AI-powered software platforms that help engineering teams understand, automate, and improve the software development lifecycle. They will build reusable tools, APIs, workflows, and interfaces that allow development teams to adopt AI-assisted development patterns without rebuilding infrastructure from scratch. They will connect data from CI/CD, deployments, approvals, security scans, quality gates, source control, work tracking, and service dependency systems into a clearer view of software change across ABC.

They will also build durable infrastructure for long-running AI-assisted workflows such as code review, change analysis, release support, planning, remediation, validation, and other multi-step engineering processes. Without this role, internal AI tooling may remain fragmented, engineering teams may build one-off solutions, software change intelligence may remain unclear, and AI-assisted engineering workflows may not become reliable, observable, or broadly adopted.