We are looking for a Senior AI Agent Engineer / AI Agent Architect to design and develop production-grade AI agent solutions, from orchestration architecture and tool integrations to backend services, observability, reliability, and engineering standards.
This role is ideal for someone with strong software engineering skills and hands-on experience building production AI/LLM solutions who wants to make a real impact on the architecture and technical direction of AI agent systems.
Requirements
- Strong commercial experience with Python, including building and maintaining production-grade applications.Hands-on experience with FastAPI.
- Practical experience with at least one AI agent framework and building solutions based on LLMs.
- Good understanding of agent orchestration, context and state management, and multi-step workflows.
- Experience designing tool schemas, tool-calling mechanisms, and integrations with APIs and other systems.
- Very good knowledge of REST APIs, including response streaming.Hands-on experience with Google Cloud Platform (GCP).
- Experience designing production-ready solutions with scalability, reliability, security, and observability in mind.
- Strong understanding of clean code principles, testing practices, code reviews, and software engineering standards.
- Ability to make independent technical and architectural decisions and clearly communicate the reasoning behind them.
- Fluent in Polish.
Responsibilities
- Design and develop AI agent orchestration architecture, including multi-step workflows, state and context management, error handling, and retry mechanisms.
- Design tools used by AI agents, including tool schemas, input/output contracts, and integrations with internal systems and external APIs.
- Build and maintain production-grade services using Python and FastAPI, including REST endpoints with response streaming.
- Design reliable and secure mechanisms for agents to interact with external services, APIs, and data sources.
- Deploy and maintain solutions on Google Cloud Platform (GCP), including deployment, scaling, monitoring, and cost optimization.
- Ensure reliability and observability of agent-based systems through logging, monitoring, and tracing of LLM and tool calls.
- Implement mechanisms for evaluating response quality and introducing appropriate safeguards, including guardrails and tool access control.
- Optimize solution performance and costs, particularly in terms of latency, token consumption, and model selection for specific tasks.
- Define and maintain engineering and coding standards within the team, including code reviews, testing practices, development conventions, and technical documentation.
- Collaborate with product and business teams to translate business requirements into effective AI agent solutions.
- Keep up with developments in the AI agent ecosystem, including MCP and multi-agent architectures, and recommend technologies and approaches suitable for production use.
Our offer
- A collaborative and supportive work environment based on partnership and knowledge sharing.
- The opportunity to work on an interesting and challenging e-commerce project in a dynamic environment.
- A real impact on the quality of the solutions being developed.
- Opportunities to develop your AI skills while gaining experience with modern systems and technologies.