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# Lead Developer - Agentic AI Platform

- **Company:** UNIQA Insurance Group AG
- **Location:** Wien, Austria (Remote available)
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Application Frameworks, Computing Platforms, Automation of Tests, Software Quality, Continuous Integration, Programming Tools, Distributed Systems, Graph Database, Python (Programming Language), Open Source Technology, Secure Coding, Software Engineering, Large Language Models, Knowledge Representation, Virtual Agents, Api Design, Code Restructuring, Network Server
- **Published:** September 14, 2026
- **Apply:** https://uniqa-it-services-gmbh.contactrh.com/jobs/6967/44438166/en_US

## About the Role

* Strong hands-on Python development experience
 * Experience developing reusable frameworks, SDKs, libraries, platform components, or developer tools
 * Deep understanding of open-source AI and agentic AI frameworks such as LangChain, LangGraph, Semantic Kernel, AutoGen, LlamaIndex, CrewAI, or comparable frameworks
 * Strong understanding of LLM-based agent architectures, including planning, tool use, routing, orchestration, reasoning patterns, and agent runtime design
 * Hands-on experience with MCP-style servers, action or skill servers, schema design, validation logic, and execution interfaces
 * Solid knowledge of RAG systems, including retrieval logic, chunking, ranking, generation, grounding, and evaluation
 * Good understanding of agent memory concepts, including vector memory, semantic memory, session context, and long-term memory patterns
 * Strong skills in API design, schema modeling, interface contracts, modular software design, and distributed systems
 * Experience with test automation, evaluation harnesses, quality gates, CI/CD, secure coding, and code quality practices
 * Familiarity with knowledge representation concepts such as ontologies, taxonomies, and knowledge graphs is beneficial

## Description

* Develop and maintain Python-based platform capabilities, reusable components, SDKs, templates, and developer tools
 * Design and implement reusable framework capabilities for agents, tools, MCP servers, orchestration, memory, RAG, model access, and evaluation
 * Implement MCP servers end-to-end, including schema design, validation logic, action execution, error handling, and interface contracts
 * Extend agent runtime capabilities, including planning, tool-use, routing, reasoning support, context handling, and orchestration patterns
 * Design and evolve RAG and knowledge access logic, including chunking, retrieval, ranking, generation, and evaluation patterns
 * Implement agent memory and context management logic, including semantic, vector-based, and session-related memory concepts
 * Build test frameworks, evaluation harnesses, and enablement tooling that allow developers to test, validate, and improve agentic AI solutions
 * Ensure clean separation between shared platform/framework capabilities and use case-specific implementation logic
 * Evaluate, integrate, and extend open-source AI and agentic AI frameworks in line with the platform architecture
 * Drive code quality, modularity, refactoring, secure coding, documentation, and maintainability of the platform codebase


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