AI Engineer (m/w/d)

About RLVNT

RLVNT counts among the most innovative communication agencies in Germany. Founded in 2014, the owner-managed agency and digital consultancy, RLVNT among others, sets new standards by combining strategic consulting with data-driven performance and artificial intelligence. With a diverse portfolio of national and international global players and love brands from industry to automotive to technology, food, crafts, and sustainability, RLVNT offers innovative communication solutions across industries for sustainable impact and customer success. Numerous awards, including the title of Business Punk Top Agency 2021 as well as PR Report Awards and German Brand Award Gold, underscore RLVNT's leading role in the communication industry.

Responsibilities

• Conceptualization and implementation of RAG systems (Retrieval-Augmented Generation) and agent-based solutions
• Practical NLP knowledge including Named Entity Recognition, Sentiment Analysis, and Information Extraction from unstructured data
• Ability to translate business requirements into viable technical AI concepts
• Seamless integration of AI systems into existing corporate landscapes
• Confident use of REST and GraphQL APIs for connecting data sources and systems
• Design of architectures for connecting diverse data sources (calendars, project tools, collaboration platforms)
• Preparation of unstructured data (e.g., from PDFs, websites) through ETL processes and chunking for vector databases
• Practical experience with vector databases such as Qdrant, SupaBase, Pinecone, or similar
• Confident use of LLM orchestration frameworks for automating AI workflows (e.g., n8n, LangChain, Langdock)
• Comprehensive experience as the primary programming language for developing and integrating AI solutions
• Practical experience with at least one of the major cloud AI platforms: Microsoft Azure AI, Google Vertex AI, or AWS (Bedrock, SageMaker)
• Knowledge in integrating AI into collaboration tools like Microsoft Copilot for Teams
• Practical experience with alternative agent frameworks like AutoGen, CrewAI, or similar
• Knowledge in advanced RAG techniques beyond vector search, e.g., Graph-RAG or multi-modal approaches
• Basic understanding of how LLMs work and their customization options
• Ability to create simple web interfaces or APIs for prototypes (e.g., with Flask, FastAPI, React)
• Creative approaches to evaluating LLM-based assistants, especially in scenarios without established test guidelines (e.g., with tools like Langfuse)
• Basic understanding of Deep Learning & Cloud Technologies
• Basic understanding of how Deep Learning models work (PyTorch/TensorFlow)
• Fundamentals of Docker and cloud-based services (AWS, Azure, GCP)
• Analytical and pragmatic solution design: Ability to find the right balance between technical feasibility and economic benefit (80/20 principle)
• Initiative and willingness to learn: Proactive familiarization with new frameworks and technological trends, actively contributing knowledge to the team
• Communication skills: Clear communication of technical concepts to various stakeholders and effective collaboration with internal and external teams
• Risk awareness: Strong understanding of LLM-specific challenges such as hallucinations, prompt injection, data privacy, and ethical implications

Qualifications

• Excellent AI Knowledge: Enthusiasm and significant experience in generative AI, and knowledge of the functionality and usage (prompting) of the most important LLMs (GPT, Claude, Bard) and applications (ChatGPT, Perplexity, HeyGen, ElevenLabs, Langdock)
• Basic experience in software development (Python) and/or data management
• Pacemaker mentality and trendsetter: Curiosity and desire to try things out, find and test new ways of using generative AI with our clients
• Project management: A high degree