D

D ONE

Data-driven value creation consultancy for enterprises

Retrieval-Augmented Generation Architectures Intern

InternshipUpdated on 10/23/2026
No salary listed
Bachelor's, Master's, PhD
Zürich, Switzerland
In Person
AI & Machine LearningNatural Language Processing & LLMs

About the job

Requirements
  • Current enrollment in a Bachelor's, Master's, or PhD programme in Computer Science, Data Science, Computational Linguistics, Engineering, Mathematics, or a comparable field.
  • Experience working with large data sets and databases.
  • Knowledge of relevant technologies and programming languages, such as Python, SQL, Git, Spark, and cloud platforms.
  • Excellent communication skills in English.
Responsibilities
  • Review the state of the art in retrieval-augmented generation and select approaches worth building on.
  • Design and implement retrieval-augmented generation components in clean, modular, well-tested Python.
  • Run the same solution across local and cloud environments and reason about the trade-offs.
  • Systematically benchmark configurations and interpret the results.
  • Document the work and present it to technical and non-technical audiences.
  • Strive to understand clients' needs.
  • Deliver results with high business value in a comprehensible form.
  • Work independently, structure progress, and involve a senior colleague when needed.
Desired Qualifications
  • Working understanding of large language models, embeddings, vector search, and the interaction between retrieval and generation.
  • Hands-on experience with orchestration libraries such as LangChain, LlamaIndex, or Haystack, and vector stores such as pgvector, Qdrant, Weaviate, Chroma, or FAISS.
  • Familiarity with document ingestion, chunking and indexing strategies, hybrid retrieval (lexical and dense), and re-ranking.
  • Software engineering discipline including modular package design, configuration management (such as Hydra or Pydantic settings), dependency management, unit testing, and continuous integration.
  • Ability to run models locally (such as Ollama, vLLM, or llama.cpp) and via hosted APIs, and to containerise workloads with Docker.
  • Exposure to at least one cloud platform (Azure, AWS, or GCP) and its managed AI and vector services.
  • Comfort with structured experimentation, including parameter sweeps, experiment tracking (such as MLflow or Weights & Biases), and reproducible runs.
  • Awareness of performance and cost considerations, including latency, throughput, token economics, and caching.
  • German language skills.

About the company

1) What the company does: D ONE is a consultancy that helps organizations create value from data by guiding corporate transformation toward an information-driven enterprise. Teams are composed of hands-on business practitioners who combine practical experience with strong academic credentials. 2) How the product works: They provide advisory services that assess a client’s data maturity, design a data-driven transformation, and guide implementation with concrete, easy-to-follow steps that translate data capabilities into business outcomes. 3) How it differs from competitors: D ONE emphasizes a practical, easy-to-do-business-with approach anchored by experienced business practitioners and solid academic insight, aiming to deliver real value rather than simply offering technology or theoretical frameworks. 4) The goal: to enable clients to realize measurable business value from data by becoming an information-driven organization through focused, doable transformation efforts.

Company Size

51-200

Company Stage

N/A

Total Funding

N/A

Headquarters

Zurich, Switzerland

Founded

2005

Get referred to D ONE

See people who can refer or advise you

Simplify Jobs

Simplify's Take

What believers are saying

  • August 20, 2026 AI Industrialization Playbook matches enterprises seeking measurable AI value now.
  • The April 7, 2026 interview directly targets failed pilot fatigue and demand for scale.
  • D ONE’s publications and conferences create inbound credibility with Swiss decision-makers in 2026.

What critics are saying

  • Accenture, Deloitte, and cloud vendors can replicate D ONE’s playbook quickly.
  • Without proprietary software, D ONE depends on consulting margins and client budget cycles.
  • If clients internalize AI operations by 2027, D ONE becomes a replaceable vendor.

What makes D ONE unique

  • Hans Peter Gränicher, 2026 CEO, sells AI industrialization, not ad hoc analytics.
  • D ONE’s Strategy-Foundation-Scale-Trust framework packages transformation into a repeatable operating model.
  • November 17, 2026 Zurich conference reinforces thought leadership inside Swiss enterprise data circles.

Help us improve and share your feedback! Did you find this helpful?

Benefits

  • Mentorship Program
  • Training Programs
  • Professional Development Budget
  • Company Social Events