Role overview
- 25 years of experience in software engineering, established in Vienna, Austria
- Active in Romania since 2007, with office in central Bucharest (Bd. Iancu de Hunedoara 54B)
- Delivering End to End IT Consulting Services - From Team Augmentation and Dedicated Teams to Custom Software Development
- We deliver scalable enterprise systems, intelligent automation frameworks, and digital transformation platforms
- Cross-industry experience by sustaining global players in BSFI (Banking, financial services and insurance), Telecom,Retail & E-commerce, Energy and Utilities, Automotive, Manufacturing, Logitics, High Tech
- Global Presence: Switzerland, Germany, Austria, Sweden, Hungary, Slovakia, Serbia, Romania, and Indonesia
- International team of 500+ software engineers
- Strategic partnerships: Microsoft Cloud Certified Partner, Tricentis Solutions Partner in Test Automation and Test Management, Creatio Exclusive Partner, Doxee Implementation Partner
- Powered by cutting-edge technologies: AI, Data & Analytics, Cloud, DevOps, IoT, and Test Automation.
- Project beneficiaries ranging from large-scale enterprises to startups
- Stable growth and revenue increase year over year, a resilient organisation in volatile IT market conditions
- Quality-first mindset, culture of innovation, and long-term client partnerships
- Global and local reach – trusted by key industry players in Europe and the US
What you'll work on
- Design, train, and optimize large language models (LLMs) and transformer architectures.
- Develop and implement agentic AI systems, including multi-agent orchestration and hierarchical agent roles (planner, executor, verifier, critic, memory manager).
- Work with agent architectures such as ReAct, Reflexion, Voyager, AutoGPT, CrewAI, and AutoGen.
- Implement and maintain agent orchestration frameworks like LangChain, LangGraph, Semantic Kernel, LlamaIndex, and Swarm.
- Design and manage multi-agent communication protocols (e.g., MCP, A2A), including message passing, coordination, and negotiation strategies.
- Balance agent autonomy with human-in-the-loop governance mechanisms.
- Apply MLOps and LLMOps best practices for deployment, monitoring, scaling, and lifecycle management of AI systems.
What we're looking for
- Deep understanding of transformer architectures, attention mechanisms, and LLM training pipelines.
- Hands-on experience with multi-agent AI systems and orchestration frameworks.
- Strong knowledge of multi-agent communication protocols and hierarchical agent design.
- Expertise in MLOps / LLMOps, including automation, monitoring, and scaling of AI/ML pipelines.
- Ability to design AI systems with controlled autonomy and governance.
- Strong problem-solving, system design, and collaboration skills.
- Experience with AI agents in production environments.
- Knowledge of emerging agentic frameworks and research in autonomous AI systems.
- Familiarity with human-in-the-loop systems and ethical AI practices.
Tags & focus areas
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