Technical Expert

Location: Prague (Hybrid); Czech Republic (Remote); UK (Remote); Ghent (Hybrid), Poland (Remote), Hungary (Remote), Romania (Remote)

Function: Software Engineering

Reports to: Manager, Esko AI

About The Role

The Esko AI team is a group of specialists focused on leveraging AI to solve valuable and often challenging customer problems that have historically resisted automation via purely rule-based approaches. To succeed in the complex domain of packaging graphics, AI agents must operate reliably according to regulatory requirements, technical specifications, brand guidelines, customer-specific conventions - and invoke expert human judgement when required. This is a complex engineering problem that goes beyond the boundaries of standard agentic scenarios.

We're looking for a Technical Expert to take technical ownership of core agentic capabilities within Esko’s AI Platform, from experimentation and design through production implementation.be a senior authority and author on agentic AI across Esko's AI Platform. This is a hands-on technical role, not a management one: you'll set direction and raise the bar through writing code, leading experiments, writing documentation, and mentorship of team members for a platform that spans multiple agentic capabilities (knowledge & reasoning, tool use and orchestration, evaluation, and safety/guardrails) and which is used by many product teams across the business.

You should bring experience from multiple agentic AI projects with a similar order of complexity in terms of the technical challenges you have successfully tackled, together with a ‘sixth sense’ for agentic AI operation to predict the approaches which are likely yield successful results as the platform grows into new domains.

What You Will Do

• Go deep on the hardest technical problems inside the agentic AI platform - the ones where progress depends on specialist expertise, not just engineering effort: data discovery & consolidation, agent planning and tool-use, retrieval and grounding, validation-before-action, conflict/ambiguity handling, and similar hard sub-problems.
• Personally design, build, and harden the platform's most technically demanding components - the pieces where correctness, edge cases, and failure modes are subtle enough to need deep, hands-on ownership rather than delegation.
• Act as the team's go-to technical expert on agentic AI and LLM systems: the person others bring their hardest \"how do we actually make this work\" problems to, providing depth on specific technical questions rather than setting overall team direction.
• Diagnose and resolve the platform's toughest technical issues - performance, reliability, correctness, and edge-case failures - where specialist knowledge is the difference between a real fix and a workaround.
• Contribute into architecture discussions, stress-testing designs against hard technical realities (scaling limits, failure modes, subtle correctness issues) that come from real specialist experience.
• Evaluate emerging techniques, frameworks, and tools in agentic AI and LLM tooling, and give the team pragmatic, evidence-based recommendations on what's worth adopting.
• Write technical deep-dives and documentation that make complex mechanisms legible to the rest of the team, so your expertise compounds rather than staying tacit.

What We Are Looking For

• Strong software engineering experience designing, building, and operating production systems in Python, TypeScript, Java, or a similar language.
• 10+ years of software engineering experience, including substantial time as a senior/staff/principal-level individual contributor architecting and operating production agentic AI systems involving multi-step reasoning, tool use, planning, or orchestration, where alignment and dependability of the agent’s output is a key success factor.
• Experience across multiple distinct agentic AI projects, able to draw on that breadth to guide technical decisions in unfamiliar contexts.
• Deep, hands-on expertise in: LLM agent frameworks and orchestration, tool-calling and validation-before-action patterns, RAG and retrieval architecture, evaluation and observability for AI systems.
• A track record of setting technical direction and shaping outcomes across teams without formal management authority.
• Sound engineering judgement on production concerns at platform scale: reliability, security, multi-tenancy, performance, and observability for services consumed by many internal teams.
• Excellent technical communication - able to write RFCs and architectural documents that align diverse stakeholders, and to move fluently between deeply technical and business audiences.
• Comfort operating with signif