Focus on GenAI: Design and implement modern RAG architectures (Retrieval-Augmented Generation), agentic workflows, and generative AI use cases.
Modeling and Integration: Select and fine-tune LLMs and integrate them into production business processes.
Foundations: While your primary focus is Generative AI, you leverage your knowledge of traditional machine learning techniques and deep learning to build hybrid solutions where LLMs alone are insufficient. You also have experience designing APIs using OpenAPI/Swagger and connecting them to Spring Boot backends to integrate Generative AI into existing applications.

Take End-to-End Ownership of Solutions

Production-Ready AI: Take GenAI applications from the initial prompt idea through prototyping to scalable deployment (LLMOps).
Integration into Existing Applications: Integrate GenAI features into our existing web applications — Angular on the frontend and Spring Boot on the backend — and actively contribute to their further development.
Data and Orchestration: Build and optimize the data foundations for agents and vector databases, as well as orchestrate complex workflows and agents.
Quality Assurance: Ensure system stability, evaluate model outputs, implement guardrails, and optimize performance.

Consulting and Collaboration

Technology Translator: Explain the difference between hype and genuine business value to stakeholders, translating complex architectures into clear, actionable recommendations. You also facilitate customer workshops, including workshops on topics such as requirements engineering.
Cross-Functional Collaboration: Work closely with business analysts and software engineers to seamlessly integrate AI into existing software ecosystems.

Continuous Development and Knowledge Sharing

State of the Art: Stay up to date with the rapid developments in LLMs, multimodal models, and agent frameworks.
Knowledge Transfer: Actively contribute to internal knowledge-sharing initiatives and prototype new features for the attempto Academy.

Frameworks: You are proficient in one or more LLM and agent orchestration frameworks or tools, such as LangChain, LangGraph, PydanticAI, Google ADK, OpenAI Agent SDK, LlamaIndex, Spring AI, or Haystack.
GenAI Stack: You have hands-on experience with prompt engineering, embeddings, and building and managing vector databases (e.g., Pinecone, Weaviate, Milvus, or Chroma).
Programming Languages: Python is your primary language for GenAI development. You also have solid knowledge of Java/Spring Boot and the Angular ecosystem (TypeScript) to integrate AI capabilities into our applications.

Technical Understanding and Foundations

Cloud and Deployment: Experience with cloud AI services (Azure OpenAI, AWS Bedrock, or Google Cloud Vertex AI), as well as Docker/Kubernetes.
Architecture: A solid understanding of APIs, microservices, and data pipelines.
AI Fundamentals: You have a conceptual understanding of how deep learning and transformer architectures work.
Backend Foundations: You have experience working with Spring Boot in combination with GenAI.
Frontend Experience: You understand how new GenAI capabilities can be presented in an application's frontend and can implement the integration yourself.
Languages: Fluent in German and English.

Ways of Working

Pioneering Spirit: You are excited to work in a field that reinvents itself every week.
Analytical Thinking: You work in a structured manner and maintain a clear overview, even when dealing with complex system architectures.
Communication: You can confidently communicate technical concepts in a clear and audience-appropriate manner.

Nice to Have

In-depth experience in MLOps or data engineering.
Project experience in regulated industries (e.g., banking or insurance).
Knowledge of frontend technologies (e.g., Streamlit, React, CopilotKit/AG-UI) for rapidly building AI demos and compelling GenAI web applications.

JobRad – leasing offer with employer subsidy
JobTicket – tax-free employer contribution
Contractually regulated training – targeted personal and professional development
Company pension plan – additional employer contribution to the insurance premium
Cool office with plenty of space for creativity – remote work from home possible depending on the project
Shaping attempto – management actively involves employees
Mentoring program – mentors for new employees
Numerous company events – summer party, Oktoberfest celebration, year-end party, and more
Knowledge transfer – various internal training and knowledge-sharing opportunities
Fit-at-work programs – health days, company runs, and more
Regional assignment – mostly local and long-term project deployment
Successful teamwork – fostered through openness and team cohesion
Innovative projects – at client sites and in the attempto Innovation Workshop

Telefon: 089 2170377-77

E-Mail: jobs@attempto.eu