Enterprise AI Architect
Salary not listed • Bucharest • Full-time
Posted 1mo ago
Job Location
Bucharest
Tech Stack
Remote Work Policy
On-site
Employment Type
Full-time
Categories
AI Agent Engineer
About the job
The opportunity involves designing and implementing end-to-end, client-specific AI architectures. This role focuses on integrating agents, models, enterprise data, applications, identity, and controls across both cloud and on-premises environments. You will translate business requirements into actionable architecture and implementation decisions, design various AI patterns including agentic workflows, RAG, and human-in-the-loop systems, and define hybrid deployment strategies considering constraints like residency, latency, security, performance, and cost. The role also includes evaluating technology choices, documenting architectural decisions and trade-offs, providing technical assurance during delivery, and collaborating with governance, Responsible AI, cyber, and privacy specialists.
Responsibilities
- Translate business and product requirements into target architectures and implementation decisions.
- Design agent, RAG, model-routing, integration, API, identity, and human-in-the-loop patterns.
- Define hybrid deployment patterns considering residency, latency, security, performance, and cost constraints.
- Evaluate technology choices and document architecture decisions, trade-offs, and non-functional requirements.
- Provide technical assurance throughout delivery and support production-readiness reviews.
- Collaborate with governance, Responsible AI, cyber, privacy, and sector specialists.
- Support proposals, client workshops, and market development.
- Contribute reusable methods, patterns, code, assets, and lessons learned.
- Coach colleagues and participate in continuous learning initiatives.
Requirements
- 8+ years in solution, enterprise, cloud, or AI architecture.
- Strong knowledge of generative AI, agentic systems, data platforms, integration, and distributed applications.
- Experience designing hybrid cloud and on-premises solutions.
- Ability to communicate architecture choices to diverse stakeholders (executives, engineers, security, business owners).
- Hands-on architecture experience with at least two agent orchestration approaches (e.g., LangChain, LangGraph, Semantic Kernel, AutoGen, CrewAI).
- Ability to design deterministic and agentic workflows, single-agent and multi-agent patterns, durable state, memory, tool calling, hand-offs, human approval, fallback, and exception handling.
- Strong knowledge of RAG and knowledge architectures, including embedding models, vector/hybrid search, reranking, metadata filtering, semantic layers, knowledge graphs, context management, and retrieval evaluation.
- Experience designing model-agnostic and multi-model architectures across managed and self-hosted models, including model routing, gateways, prompt/policy layers, structured outputs, caching, and latency/cost trade-offs.
- Practical knowledge of MCP and API-based tool integration, event-driven architecture, identity delegation, secrets management, auditability, and zero-trust patterns for agents.
- Experience producing architecture artifacts for hybrid deployment using cloud AI platforms, containers, Kubernetes, private networking, on-premises data sources, and locally hosted inference.