Job Description:

We are seeking a motivated and hands-on NLP & Document Intelligence Engineer to join our team and contribute to the development of AI-driven document processing solutions in the life sciences domain. This mid-level role focuses on applying Natural Language Processing (NLP) techniques to extract structured knowledge from complex scientific, clinical, and regulatory documents.

You will work on real-world use cases involving entity and relationship extraction, document understanding, and knowledge graph creation, using a combination of rule-based NLP and LLM-based approaches. The role places strong emphasis on production-ready NLP pipelines built on Azure, and close collaboration with data, semantic, and life science experts.

This position is ideal for someone who already has practical NLP experience and is ready to deepen their expertise in life sciences document intelligence.

Key Responsibilities:

1. Life Sciences Document Processing

• Process and analyze life sciences-related documents, such as scientific publications, clinical trial documents, regulatory submissions, study reports, and internal research documentation.
• Build and maintain document ingestion and processing pipelines for unstructured and semi-structured content (PDFs, Word files, structured text exports).
• Apply NLP techniques to extract relevant scientific and biomedical information while accounting for domain-specific terminology and document structures.

2. NLP & Information Extraction

• Implement entity extraction and normalization for life sciences concepts (e.g. compounds, targets, diseases, studies, endpoints, organizations).
• Develop relationship extraction logic to identify meaningful connections between extracted entities across documents.
• Combine rule-based NLP techniques (patterns, linguistic rules) with LLM-based approaches to achieve reliable and explainable extraction results.
• Contribute to the transformation of NLP outputs into graph-oriented representations.

3. AI & NLP Engineering

• Work with LLM-based NLP workflows, including prompt engineering and hybrid pipelines (e.g. retrieval-augmented approaches).
• Support evaluation and continuous improvement of NLP models and extraction pipelines.
• Implement reusable NLP components with a focus on robustness, traceability, and maintainability.

4. Cloud & Pipeline Development (Azure)

• Develop and operate NLP pipelines on Azure, leveraging cloud-native services and managed AI components.
• Contribute to the implementation of ETL/ELT-style pipelines for document processing and NLP enrichment.
• Monitor, troubleshoot, and optimize NLP workflows running in production environments.

5. Collaboration & Ways of Working

• Collaborate closely with semantic data engineers, data engineers, and life sciences domain experts.
• Work in an Agile/Scrum environment, contributing to sprint planning, implementation, and reviews.
• Document NLP workflows, extraction logic, and pipeline configurations clearly and consistently.
• Contribute to DevOps practices, ensuring continuous integration and deployment of data solutions.

Required Qualifications and Skills:

• Practical experience with Natural Language Processing applied to document processing use cases.
• Prior exposure to life sciences–related documents, such as scientific literature, clinical trial documentation, or regulatory texts.
• Hands-on experience with entity extraction and relationship extraction.
• Familiarity with both rule-based NLP approaches and LLM-based NLP techniques.
• Experience building or contributing to data and NLP pipelines in Azure.
• Proficiency in Python and commonly used NLP libraries and frameworks.
• Basic understanding of graph-based data representations and how extracted knowledge can be structured as entities and relationships.
• Experience working in Agile and collaborative development environments.
• Strong attention to detail and ability to work with complex, domain-specific data.

Desired Personal Attributes:

• Interest in applying NLP and AI to life sciences and biomedical data.
• Structured and methodical working style, with a focus on quality and reproducibility.
• Team-oriented mindset and willingness to learn from both technical and domain experts.
• Proactive attitude and motivation to grow into more advanced NLP and AI responsibilities.

What we offer

• Hybrid work model and flexible working schedule that would suit night owls and early birds
• Excellent compensation package
• Attractive social benefits package
• Possibilities of career development and the opportunity to shape the company future
• An employee-centric culture directly inspired by employee feedback - your voice is heard, and your perspective encouraged 
• Different training programs to support your personal and professional development
• Work in a fast growing, international company
• Friendly atmosphere and supportive Management team

If you have a passion for working with cutting-edge technologies and contributing to impactful projects in the life sciences sector, we would love to hear from you.

Apply Now to join our innovative team and make a difference in the world of semantic data engineering!