AI Solution Architect
On-site · Cluj-Napoca, Cluj County, Romania
Job Summary
AI Solution Architect leading the design, development, and scaling of enterprise-grade AI and agentic solutions within the Enterprise AI Center of Excellence. Responsible for end-to-end architecture across data, models, orchestration, security, deployment, and operations; translating business problems into technical architectures; prototyping and hardening solutions to production standards; building multi-agent systems and scalable agents that integrate with ERP and other enterprise platforms; applying guardrails, human-in-the-loop controls, and governance checkpoints; collaborating across platform, security, and application teams; and creating reusable CoE assets and reference architectures.
Required Qualifications
- Proven hands-on experience building Generative AI and multi-agent solutions for complex business process automation
- Strong understanding of agent evaluation beyond model accuracy, including task success, tool selection, and reasoning quality
- Experience with AI Ops / Agent Ops, including monitoring behavior, cost, drift, and failure modes in production
- 8-10 years of experience designing and building enterprise-scale systems, ideally involving ERP or similarly complex platforms
- Strong experience with Cloud and SaaS architectures, including identity, security, networking, and deployment
- Hands-on expertise with APIs, integration patterns, workflow orchestration, CI/CD, containerization, and infrastructure as code
- Solid grounding in LLMs, embeddings, RAG patterns, vector search, prompt design, and evaluation methods
- Experience with open-source AI and agent orchestration frameworks and production-grade observability tools
- Strong software engineering discipline, including clean interfaces, testability, and versioning
- Bachelor’s degree or equivalent experience in Computer Science, Software Engineering, or a related field
Desired Qualifications
- Bachelor's degree or equivalent experience in Computer Science, Software Engineering, or a related field
- Experience defining and operating enterprise AI governance models, including architecture reviews and production readiness controls
- A track record of building reusable enterprise assets that accelerate AI adoption across teams
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