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AI Application Engineer - AI Products (LLM & RAG) (m/f/d)
Summary by AIEngineer.careers
AI Application Engineer - AI Products (LLM & RAG) (m/f/d) is a AI Application Engineer role (full-time). with Machine Learning Reply. in BERLIN, DE. Imported listing (source: bookingagency.io). Apply on the employer's site (bookingagency.io).
Imported listing (source: bookingagency.io) · Apply on bookingagency.io
BERLIN · DE
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Full-time
MID
The sections below reproduce the third-party job description for reference. AIEngineer.careers does not write or control this text.
Imported job description
Sourced from bookingagency.io
Machine Learning Reply is seeking an AI Application Engineer to build user-facing AI products and scalable digital solutions for enterprise clients. This role focuses on integrating LLMs, RAG systems, and backend services to create production-ready AI applications like copilots and semantic search platforms. You will work at the intersection of AI engineering, product development, and cloud deployment within a collaborative global network.
Responsibilities
- Design and develop AI-powered applications such as enterprise assistants and AI copilots
- Build LLM-powered applications using Retrieval-Augmented Generation (RAG) and modern frameworks
- Develop end-to-end AI products integrating LLM APIs, enterprise data sources, and backend services
- Implement vector search, embeddings pipelines, and knowledge retrieval systems
- Deploy AI systems to cloud platforms using DevOps practices and ensure observability
Requirements
- Degree in Computer Science, Software Engineering, Data Science, or comparable field
- Strong programming skills in Python and modern backend frameworks
- Experience building applications with AI, machine learning, or generative AI technologies
- Familiarity with RAG and vector databases
Machine Learning Reply
München · DE · 96+ employees
Machine Learning Reply is an IT consulting company delivering end-to-end AI and data-science solutions. Its work spans strategy, data engineering, machine learning, NLP, computer vision, cloud-native implementation, generative AI, custom development, and upskilling.
