Software Development
Your Mission: Next-Generation Intelligent Systems
Design and Implement AI Solutions
Focus on GenAI: Conceptualize and implement modern RAG architectures (Retrieval Augmented Generation), agent-based workflows, and generative AI use cases.
Modeling & Integration: Select and fine-tune LLMs and integrate them into productive business processes.
Foundation: While your focus is on Generative AI, you leverage your knowledge of classical machine learning and deep learning to create hybrid solutions where LLMs alone are not sufficient.
Ownership of End-to-End Solutions
Production-Ready AI: You take GenAI applications from the initial prompt idea through prototyping to scalable deployment (LLMOps).
Data & Orchestration: Build and optimize data foundations for agents and vector databases, and orchestrate complex workflows and agents.
Quality Assurance: Ensure stability, evaluate model outputs (guardrails), and optimize performance.
Advisory & Collaboration
Technology Translator: You explain to stakeholders the difference between “hype” and real business value and translate complex architectures into clear decision-making proposals.
Interdisciplinary Work: Collaborate closely with business analysts and software engineers to seamlessly embed AI into existing software ecosystems.
Continuous Learning & Knowledge Sharing
State-of-the-Art: You monitor rapid developments in LLMs, multimodal models, and agent frameworks.
Knowledge Transfer: Actively contribute to internal formats and prototype new features for the attempto Academy.
Technical Profile (Focus on GenAI)
Frameworks: You are confident in working with one or more LLM/agent orchestration tools such as LangChain, LangGraph, PydanticAI, Google ADK, OpenAI Agent SDK, LlamaIndex, or Haystack.
GenAI Stack: Practical experience with prompt engineering, embeddings, and building and managing vector databases (e.g., Pinecone, Weaviate, Milvus, or Chroma).
Language Skills: Excellent Python knowledge forms your foundation.
Technical Understanding & Fundamentals
Cloud & Deployment: Experience with cloud AI services (Azure OpenAI, AWS Bedrock, or GCP Vertex AI) as well as Docker/Kubernetes.
Architecture: Solid understanding of APIs, microservices, and data pipelines.
AI Fundamentals: You understand the mathematics behind deep learning and have worked with libraries such as PyTorch or TensorFlow, which helps you understand GenAI models in depth.
Work Style
Pioneering Spirit: You are eager to work in a field that reinvents itself every week.
Analytical Skills: You work in a structured manner and maintain an overview even in complex system architectures.
Communication: You can convey technical concepts confidently and appropriately for your audience and have excellent German and English skills.
Nice to Have
Advanced experience in MLOps or data engineering.
Project experience in regulated environments (e.g., banking, insurance).
Knowledge of frontend technologies (e.g., Streamlit, React, Copilotkit/AG-UI) for rapid creation of AI demos and compelling GenAI web apps.
attempto has been very successful in the conception and implementation of complex IT projects since 2006. We are a strong partner for banks and insurance companies. We also support forward-thinking projects in industry and retail. More than 150 employees actively contribute at our locations in Munich, Karlsruhe, and Munster. In the attempto Innovation Manufactory at WERK3, we explore the latest trends and technologies. Digitalisation, sustainability, and social engagement shape our culture.
