Job Summary
This role entails the design and implementation of software solutions to optimize agent systems, utilizing advanced technologies such as RAG architectures and LLMs.
* Define agent behavior in MCP-based systems through prompt engineering
* Optimize RAG structures (e.g. LangChain libraries)
* Develop and fine-tune small, domain-specific LLMs
* Design architecture for MCP communication structures
* Extend agent systems via A2A protocols
* Develop knowledge graphs, including integration with RAG pipelines
* Evaluate and benchmark AI agents
The ideal candidate will have a strong background in computer science, electrical engineering, or a related field, along with experience in Python development and AI frameworks.
Key Qualifications
* Ability to work independently and collaboratively within a team
* Proficiency in container technologies, sandbox setups, and continuous integration
* Excellent communication skills and a willingness to learn