Software Engineer (AI)

TL;DR

Software Engineer (AI): Building core agentic technology for data transformation platforms with an accent on multimodal dataset integration and AI-driven workflows. Focus on designing scalable data pipelines, implementing robust engineering practices for ML systems, and optimizing performance in high-stakes biological research environments.

Location: Must be based in the UK or Germany, or able to work from the London office

Company

An AI-driven biotechnology company building Biology Super Intelligence (BASI) through multimodal patient data and advanced language models to accelerate drug discovery and clinical diagnostics.

What you will do

• Lead the development of core components for the Data Transformation Agent (DTA) platform.
• Design, implement, and maintain complex data orchestration workflows using Apache Airflow.
• Manage deployment and integration of AI agents within the broader infrastructure.
• Enforce high engineering standards through TDD, code reviews, and robust deployment practices.
• Collaborate with research engineers to resolve bottlenecks and optimize platform performance.

Requirements

• Must be based in the UK or Germany.
• 3+ years of professional software engineering experience.
• Deep expertise in Python and Linux/Unix environments.
• Solid understanding of LLMs and Agentic Systems principles.
• Experience with multi-omics or complex multimodal datasets.
• Familiarity with cloud platforms (GCP/AWS/Azure) and containerization (Docker/Kubernetes).

Nice to have

• Practical experience with Apache Airflow and distributed computing.
• Familiarity with spatial transcriptomics data.
• Contributions to Open Source projects or machine learning publications.
• Experience with deep learning frameworks like PyTorch or TensorFlow.

Culture & Benefits

• Flexible work organization policies.
• Friendly and informal work environment.
• Opportunity to work within a highly skilled, international scientific team.