Beroe Inc

AI Engineer (Agentic AI & LLM Systems)

Berlin AI Campus, Munich
Tech Stack
PythonClaudeOpenAILLaMAMistralLangChainHugging FaceTransformersDockerTerraform PyTorchTensorFlowscikit-learnXGBoostLangGraphFAISSPineconeOpenSearchCrewAIAutoGenSwarm
Language Requirements
English
Requirements
Senior Seniority
6+ years Experience
No Degree
Remote Policy

Hybrid

We are looking for an experienced AI Engineer to join our growing AI team at Beroe X nnamu. You’ll play a key role in developing intelligent, agentic AI systems using cutting-edge large language models (LLMs), multi-agent orchestration, and retrieval-augmented generation (RAG). 

This is a hands-on role combining software engineering, ML/NLP expertise, and a passion for building next-gen autonomous agents. You’ll collaborate closely with AI leads, backend engineers, data engineers, and product managers to bring scalable and intelligent systems to life—integrated into real-world procurement and business applications.

Key Responsibilities

  • Design and implement agentic AI pipelines using LangGraph, LangChain, CrewAI, or custom frameworks
  • Build robust retrieval-augmented generation (RAG) systems with vector databases (e.g., FAISS, Pinecone, OpenSearch)
  • Fine-tune, evaluate, and deploy LLMs for task-specific applications
  • Integrate external tools and APIs into multi-agent workflows using dynamic tool/function calling (e.g., OpenAI JSON schema)
  •  Develop memory modules such as short-term context, episodic memory, and long-term vector stores
  • Build scalable, cloud-native services using Python, Docker, and Terraform
  • Collaborate in agile, cross-functional teams to rapidly prototype and ship ML-based features
  • Monitor and evaluate agent performance using tailored metrics (e.g., success rate, hallucination rate)
  • Ensure secure, reliable, and maintainable deployment of AI systems in production environments
  • 6–8 years of professional experience in machine learning, NLP, or software engineering• Strong proficiency in Python and experience with ML libraries like PyTorch, TensorFlow, scikit-learn, and XGBoost
  • Hands-on experience with LLMs (e.g., GPT, Claude, LLaMA, Mistral) and NLP tooling such as LangChain, HuggingFace, and Transformers
  • Experience designing and implementing RAG pipelines with chunking, semantic search, and reranking
  • Familiarity with agent frameworks and orchestration techniques (e.g., planning, memory, role assignment)
  • Deep understanding of prompt engineering, embeddings, and LLM architecture basics
  • Design systems with role-based communication, coordination loops, and hierarchical planning. Optimize agent collaboration strategies for real-world tasks.
  • Solid foundation in microservice architectures, CI/CD, and infrastructure-as-code (e.g., Terraform)
  • Experience integrating REST/GraphQL APIs into ML workflows
  • Strong collaboration and communication skills, with a builder’s mindset and willingness to explore new approaches

Bonus Qualifications
  • Experience with RLHF, LoRA, or parameter-efficient LLM fine-tuning
  • Familiarity with CrewAI, AutoGen, Swarm, or other multi-agent libraries
  • Exposure to cognitive architectures like task trees, state machines, or episodic memory
  • Prompt debugging and LLM evaluation practices
  • Awareness of AI security risks (e.g., prompt injection, data exposure)

At Beroe X nnamu GmbH, we prioritize building a fulfilling and flexible work experience for our team. Here’s what we offer:
  • 4-Day Work Week & Up to 24 Days Off – More time to recharge and explore
  •  Competitive Compensation – Fair salary and full-time benefits
  • Flexible Work Arrangements – Remote-friendly culture with hybrid options in Berlin or Munich
  • Professional Development – Access to training, AI certifications, and learning budgets
  • Work Abroad Options – Up to 8 weeks/year remote from select countries (with travel insurance)
  • Collaborative Culture – Quarterly team lunches, bi-annual company meetups, and open idea-sharing
  •  Autonomy & Impact – Build industry-defining systems with real-world applications

We operate on a hybrid model with offices in Berlin and Munich, anchored by a 32-hour, 4-day workweek. This means:
  • In-Office Collaboration – 2 office days/week • Flexible Hours –
  • Manage your workday in a way that meets both your needs and team goals

Our Culture
We’re passionate about building cutting-edge AI tools while fostering a collaborative and inclusive environment. Diverse teams create better solutions, and we welcome applicants from all backgrounds. Your ideas and curiosity will shape the future of our products.