Own the technical implementation and framework development of the Agentic AI Platform
Develop and maintain Python-based platform capabilities, reusable components, SDKs, templates, and developer tools
Design and implement framework capabilities for agents, tools, MCP servers, orchestration, memory, RAG, model access, and evaluation
Implement MCP servers end-to-end, including schema design, validation, action execution, error handling, and interface contracts
Extend agent runtime capabilities for planning, tool use, routing, reasoning, context handling, and orchestration
Design and evolve RAG and knowledge access logic, including chunking, retrieval, ranking, generation, and evaluation
Implement agent memory and context management, including semantic, vector-based, and session-related memory
Build test frameworks, evaluation harnesses, and enablement tooling for testing and improving agentic AI solutions
Separate shared platform/framework capabilities from use-case-specific implementation logic
Evaluate, integrate, and extend open-source AI and agentic AI frameworks
Drive code quality, modularity, refactoring, secure coding, documentation, and maintainability
Requirements
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 ontologies, taxonomies, and knowledge graphs is beneficial
Core Competencies Demonstrates expertise in Python development and the design of reusable frameworks and SDKs for AI platforms. Proficient in implementing agent architectures, memory management, and evaluation systems while ensuring code quality and maintainability.
Highest-signal resume keywords
Python Development
Framework Development
Open-Source AI Frameworks
MCP Server Implementation
RAG Systems Knowledge
Hard Skills
Python
Framework Development
SDK Development
API Design
Schema Design
RAG Systems
Agent Memory Management
Test Automation
Modular Software Design
Distributed Systems
Industry Keywords
Agentic AI
MCP Servers
Evaluation Harnesses
Knowledge Graphs
Ontologies
Taxonomies
Tools & Technologies
LangChain
LangGraph
Semantic Kernel
AutoGen
LlamaIndex
CrewAI
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Lead Developer – Agentic AI Platform in Wien Arbeitgeber: Jobtailor
Als Front Office Supervisor in unserem dynamischen Team bieten wir Ihnen die Möglichkeit, in einem unterstützenden und freundlichen Arbeitsumfeld zu wachsen. Wir legen großen Wert auf die berufliche Entwicklung unserer Mitarbeiter und bieten regelmäßige Schulungen sowie die Chance, Verantwortung zu übernehmen. Unsere Lage ermöglicht es Ihnen, Teil einer lebendigen Gemeinschaft zu sein, während Sie gleichzeitig die Standards unseres Franchise-Partners einhalten und unseren Gästen einen unvergesslichen Aufenthalt bieten.
