DevOps Engineer
AI Solution Architect - Budapest - 12 months
Budapest
Apply on the employer's siteRole description
We are looking for an experienced
AI Solution Architect
to design, lead, and deliver end-to-end Artificial Intelligence and Generative AI solutions, taking concepts from business discovery through to production-ready deployment.
This role is ideal for someone who combines deep
enterprise architecture expertise
with modern
software engineering practices
and a strong understanding of
Generative AI, Machine Learning, Agentic AI, and AI-powered business applications
.
We're particularly interested in professionals who stay ahead of emerging trends, including
Agentic AI, multi-agent architectures, agent harnesses, LLM evaluation frameworks, AI-assisted software development, and coding agents such as Codex and Claude Code
. Experience with
Computer Vision
technologies is highly desirable.
Responsibilities:
- Discovery & Shaping:
Lead stakeholder workshops, translate business needs into MVP scopes, and map out scalable implementation roadmaps. - End-to-End Architecture:
Design and document (C4 diagrams, API contracts) robust cloud architectures covering application, data, and LLM layers. - Advanced AI Design:
Build cutting-edge GenAI and Agentic systems using RAG, embeddings, multi-agent orchestration, and context/memory management. - Technical Leadership:
Guide cross-functional delivery teams (DevOps, MLOps, Data), unblock technical issues, and champion clean code and Git-based workflows. - Security & LLMOps:
Implement security-by-design, safety evaluation harnesses (hallucination checks, prompt injection defense), and automated testing.
Requirements:
- Experience:
7+ years in IT/Software Engineering, including 5+ years in Solution Architecture or technical leadership, with a track record of delivering enterprise-grade AI, cloud, or automation solutions. - Education:
Bachelor's/Master's degree in Computer Science, AI, Data Science, or a related field (or equivalent practical experience). - AI & Data Tech Stack:
- Deep practical knowledge of GenAI & Agentic Architecture (RAG, vector databases, multi-agent orchestration, tool calling, LLM evaluation, and safety guardrails).
- Core data engineering proficiency (data modeling, pipelines, relational/NoSQL).
- Python programming skills; familiarity with cloud-native stacks (Azure preferred-Azure OpenAI, AI Search).
- Pluses: Computer Vision (OCR, object detection) and frontend basics (React/Angular).
- Architecture & Delivery:
Strong foundation in backend systems, secure API/modular design, distributed integration patterns, Agile delivery, and DevOps/MLOps/LLMOps pipelines (CI/CD, versioning, monitoring). - Documentation & Safety:
Experience creating clear C4 diagrams, technical specs, and runbooks while enforcing responsible AI, privacy, and security-by-design.
Nice-to-Have Skills:
- Cloud & Integration: Hands-on experience with Azure-native AI services, API management, enterprise integration platforms, and identity/secure access patterns.
- Advanced AI: Familiarity with Computer Vision, agent/orchestration frameworks, TOGA, LLM observability, and evaluation tools.
- Governance & Standards: Experience setting up reusable AI architecture blueprints/standards, data privacy protocols, responsible AI, and AI-specific threat modeling.
Interested? Please apply and let's connect!
Razvan Tarus
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