AI Engineer AgenticOps

About the Role

Role SummaryThis is an AI Engineering role with a strong platform and operations focus. We are looking for engineers coming from DevOps, platform engineering, MLOps, LLMOps, AIOps, or software engineering backgrounds who want to specialize in operating modern AI and agentic systems.The ideal candidate does not need to already hold an “AgentOps” title. Strong experience operating cloud-native systems, combined with exposure to AI or ML workloads, is equally relevant.

Responsibilities

• Build reusable deployment, CI/CD, and operational patterns for AI agents, models, prompts, tools, configurations, and evaluations.
• Implement observability across agent execution, model calls, tool usage, quality, latency, failures, and cost.
• Establish automated evaluation and validation gates throughout the AI delivery lifecycle.
• Implement secure access, environment management, governance, release controls, recovery, and production-support p

What We Are Looking For

• Approximately 2 to 5 years of experience in AI Engineering, MLOps, Data Engineering, DevOps, SRE, Platform Engineering, Software Engineering, or a related technical field.
• Hands-on experience with cloud infrastructure, CI/CD, containers, Infrastructure as Code, monitoring, and production troubleshooting.
• Good understanding of GenAI and agentic systems, including agent workflows, tool usage, RAG, model integrations, evaluations, guardrails, and common failure modes.
• An evidence-based engineering mindset, with practical knowledge of testing, experimentation, observability, quality metrics, and continuous improvement.
• Familiarity with the operational lifecycle of AI applications, including versioning, deployment, evaluation, monitoring, rollback, security, and cost management.
• Programming or scripting experience in Python, PowerShell, Bash, TypeScript, Go, or another applicable language.
• Ability to build reusable and secure platform capabilities rather than one-off deployment solutions.

Any of the Following Would Be a Plus

• Experience with Azure, Azure AI Foundry, Azure OpenAI, Azure Kubernetes Service, Azure Container Apps, or comparable cloud and AI platforms.
• Experience with LLMOps, AgentOps, MLOps, AI evaluation pipelines, model gateways, distributed tracing, or AI application observability.
• Familiarity with Terraform or Bicep, GitHub Actions or Azure DevOps, OpenTelemetry, Application Insights, Prometheus, Grafana, MLflow, or equivalent tooling.

Benefits & Perks

• We value your time and lifestyle preferences, so you can choose whether you want to work entirely remotely or from our offices in Cluj-Napoca, Oradea and Bucharest.
• Access to learning through our internal platform – Precipio
• Private health insurance provided by Medicover
• Work from home fixed monthly budget
• Flexible benefits through the Edenred Benefit platform
• Sports benefit: reimbursement up to 150 lei/month for activities like gym, football, climbing, etc.