AI Systems Engineer

About the Role

Our client runs a multi-brand healthcare operation supported by a deeply integrated AI agent ecosystem — not chatbots bolted on as an afterthought, but a network of specialized agents embedded into daily operations across call center, billing, marketing, and recruiting: routing, data quality, candidate sourcing, process automation, reporting, and more. The system is already live and growing.

We're looking for someone who can own and evolve this ecosystem company-wide, and provide light operational oversight across the departments it touches. This is not a traditional manager role. The right person is an engineer at heart who happens to coordinate across teams — not the other way around.

Compensation: 12,000 RON – 15,000 RON / month

What You'll Do:

• Own the AI agent ecosystem end-to-end. Every integration, every workflow, every data flow across every department. Know what each agent does, why it exists, and where it breaks. Propose and implement improvements.
• Partner with department leads (call center, billing, marketing, recruiting) to identify manual processes, prioritize automation opportunities, and ship them. You don't replace these leads — you make them faster.
• Provide cross-department operational oversight. Track department-level KPIs, surface bottlenecks, and coordinate fixes that span teams. You're the connective tissue between operations and systems.
• Manage CRM operations. HubSpot is the backbone across departments. You'll maintain workflows, automation rules, data hygiene, and reporting pipelines. Prior HubSpot experience is strongly preferred.
• Build and maintain automations. Using tools like n8n, Zapier, and custom integrations. You'll identify manual processes and systematically eliminate them — regardless of which team owns them.
• Evaluate and adopt new tools. The landscape moves fast. You're expected to continuously scout for better alternatives — better models, better integrations, better architectures — and make the case with data.
• Understand and work with MCP (Model Context Protocol). You know what MCP servers are, which ones exist, and how to wire them into agent workflows. If you've built or configured MCP integrations before, say so.
• Report daily. Produce structured end-of-day reports that capture the state of ongoing work, including the context of AI systems you've interacted with, in a format that enables continuity across sessions.

What We're Looking For:

• 3+ years implementing AI agent systems in a production environment — not just prompting, but building, deploying, monitoring, and iterating.
• Hands-on experience with CRM platforms (HubSpot preferred), workflow automation (n8n, Zapier), and integration architecture.
• Familiarity with the AI tooling ecosystem — LLMs, agent frameworks, MCP, API orchestration. You should be able to name the tools you've used and explain why you chose them.
• Cross-functional fluency. You've worked across departments before — operations, sales/marketing, support, finance — and you can speak the language of non-technical leads without losing the engineering rigor.
• Obsessive attention to detail. You notice when a workflow drops a record. You check the logs before anyone asks.
• Performance-driven. You measure everything. You set targets, track them, and course-correct when numbers slip.
• Not easily intimidated by complex systems. Our client's AI infrastructure is extensive and touches every department. You should walk in and feel curious, not overwhelmed.
• Operations management experience across multiple functions is a plus, but secondary to the above. We can teach operations; we can't teach the engineering mindset.

Interview Process

During the interview, we'll walk you through parts of our existing system architecture. We want to see how you react — what questions you ask, what improvements you spot, what concerns you raise. Come prepared to discuss:

• AI agent systems you've built or operated
• How you've integrated AI into business workflows
• Your approach to evaluating and adopting new tools
• A specific automation you built that you're proud of

How to Apply

Send your CV and a brief note (max 300 words) answering: "Describe an AI system you built that is currently running in production. What does it do, how is it architected, and what would you change today?"

BE AWARE: Applications without the note will not be taken into consideration. You can add it as an extra page for your resume, or simply link it in your CV.