Senior AI Engineer (m/f/d)

Meyandy LLC; Berlin; Hybrid; EUR 90.000 - 120.000; Vollzeit

Zusammenfassung

Artefact, a global AI and data consulting company, is looking for a Senior AI Engineer (m/f/d) to join the tech team full-time. Ideally located in Hamburg, Munich, Berlin, or nearby, but if you are based elsewhere in Germany and a great fit, we would still love to hear from you.

You will innovate, build, train, and collaborate on real-world AI projects using LangChain, LlamaIndex, and OpenAI APIs, delivering production-ready solutions across industries.

Qualifikationen

• Degree in CS/AI or related field.
• 3+ years in ML/AI engineering with production projects.
• Proficiency in Python and cloud AI services (GCP/AWS/Azure).
• Experience with ML lifecycle, DevOps, and MLOps basics.

Aufgaben

• Innovate by identifying AI use cases and drive projects from concept to production.
• Build end-to-end solutions using data, LLMs, and modern AI tech.
• Train models, tune prompts, and share knowledge within the team.
• Collaborate with clients and stakeholders to balance tech and business value.

Kenntnisse

Python

ML

Cloud services

LLMs

Docker/Kubernetes

LangChain/Vector tools

Ausbildung

Bachelor's or Master in CS/AI/Data Science

Tools

LangChain

PydanticAI

MCP servers

RAG pipelines

Vector DBs

Jobbeschreibung

Artefact, a global AI and data consulting company with rapid growth, is looking for a creative and tech-savvy Senior AI Engineer (m/f/d) to join the tech team full-time. Ideally, you are located in Hamburg, Munich, Berlin or nearby - but if you're based elsewhere in Germany and a great fit, we would still love to hear from you. Could this be you?

Our data & AI experts develop production-ready, scalable solutions that bring real business value to our clients. You’ll work in interdisciplinary teams of data scientists, engineers, analysts and consultants to shape the future of data- and AI-driven products.

Your responsibilities:

Innovate.You’ll help identify business needs, explore data and AI use cases, and drive projects from idea to production - whether it’s a proof-of-concept or a scalable solution.

Build.You’ll own your work end-to-end - from concept and architecture to implementation, optimization, and delivery. You design smart, robust solutions using data or LLMs and other AI technologies.

Train.You’ll stay ahead of the curve - experimenting with new models, prompt engineering, fine-tuning, and tools. You’ll also share your knowledge within the team and benefit from our partners’ training offers (Google, AWS, etc.).

Collaborate.You’ll work closely with clients, product owners, and non-technical stakeholders, balancing technical excellence with practical business impact.

Gain broad experience:

• Work on 1-3 projects per year across different industries and use cases - from customer service automation to knowledge management and internal tools.
• Build real-world data and AI applications using modern tools like LangChain, PydanticAI, MCP servers, RAG pipelines, vector databases (e.g. FAISS, Weaviate), LlamaIndex, Vertex AI, OpenAI APIs, and Hugging Face models.
• Shape the way clients use data and AI, driving innovation and best practices in production environments.

Your mindset:

• Curious & forward-thinking. You are passionate about solving complex problems using cutting-edge AI and data technologies.
• Hands-on. You have experience with LLMs (e.g. OpenAI, Claude, Gemini, LLaMA), prompt engineering, API integration, and ML frameworks.
• Holistic. You understand the full ML lifecycle, including data preparation, model deployment, evaluation, and monitoring.
• Communicative. You can break down technical concepts for diverse audiences in English and ideally in German as well.
• Supportive. You coach junior team members, provide constructive feedback, and actively contribute to our culture of learning.

Profile:

• Degree in computer science, AI, data science or similar field.
• Experience: 3+ years of experience in machine learning or AI engineering, with hands-on AI projects in production.
• Proficiency in Python and cloud-based AI services (GCP, AWS, or Azure).
• Solid understanding of data analysis/engineering and AI-specific components like RAG, prompt design, fine-tuning, embeddings, and model evaluation.
• Familiar with DevOps and ML-Ops best practices (Docker, Kubernetes, CI/CD).
• Strong problem-solving skills, a sense of ownership, and a structured approach to work.
• Languages