useblocks is redefining the future of engineering workflows by enabling “Engineering-as-Code.” From aerospace to automotive to medical, global leaders like BMW , Bosch , CARIAD and Mercedes-Benz trust our tools for safety‑critical systems. Our open‑source project, Sphinx-Needs , has grown to over 341,000 monthly downloads , setting the standard for documentation and traceability management.

Your Role

We are looking for an exceptional AI Engineer to design, implement, and scale next‑generation multi‑agent systems powered by Large Language Models (LLMs). You’ll play a pivotal role in advancing useblocks’ AI strategy—creating autonomous agent ecosystems that drive traceability, automation, and contextual intelligence across highly regulated software environments.

This role blends deep research with practical implementation, and offers the opportunity to work on privacy‑first, local‑first solutions in collaboration with our engineering and open‑source communities.

Key Responsibilities

Research, design, and implement multi‑agent LLM‑based architectures to tackle real‑world engineering and traceability challenges.
Build algorithms for agent communication, collaboration, and task execution in complex, evolving environments.
Explore federated learning to enable on‑device training of local models, later merged into global architectures—without exposing user data.
Interface with internal toolchains (e.g., ubCode , ubTrace ) and customer systems to integrate AI models into real‑world workflows.
Design and fine‑tune LLMs using PEFT , LoRA , and similar lightweight adaptation strategies.
Work with agentic retrieval‑augmented generation (RAG) setups connected to VectorDBs , GraphDBs (e.g. Neo4j) , and documentation sources.
Connect models to customer environments using APIs, CI pipelines, and modern MLOps practices.
Stay up‑to‑date with advances in LLM architectures, agent frameworks, and deployment strategies.

Our Stack

Languages: Python (must‑have), Go, Rust (optional)
Frameworks: PyTorch or TensorFlow (deep experience in one preferred)
AI Ops: DevOps & MLOps pipelines, model serving, evaluation, and CI/CD integration

Who You Are

MSc or PhD in Computer Science, Machine Learning, AI, or a related field
Proven experience in building multi‑agent AI systems and training LLM‑based models
Strong proficiency in Python and deep experience in either PyTorch or TensorFlow
Experience with one or more open‑source agent frameworks (e.g., LangGraph, Autogen, CrewAI, LlamaIndex)
Strong grasp of toolchain integration , data parsing , and connecting models to real systems
Knowledge of federated learning and local‑first LLM deployments
Familiar with DevOps and MLOps practices , including containerized model deployment and lifecycle management
Fluent in English required—proficiency in German or other European languages is a plus

Soft Skills

Driven by curiosity, autonomy, and purpose
Humble, self‑motivated, and collaborative
Strong communication skills and a desire to mentor others
Aligned with open‑source values and ethical AI principles
Committed to making meaningful, lasting impact through software
Self‑organized and target/goal oriented

Why Join Us?

Build foundational AI systems for traceability, compliance, and developer productivity
Contribute to tools used by global engineering leaders and thousands of developers
Be part of a mission‑driven team at the intersection of AI, open‑source, and safety‑critical systems
Remote‑first culture with flexible scheduling
Competitive compensation that values expertise and innovation

How to Apply

Ready to shape the future of engineering workflows? Send us your resume and a short note about your interest to . We’d love to hear from you!

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