Location: Remote from EUROPE
About the Company
Our client is a global, science-driven biopharmaceutical company (top 10 worldwide) focused on discovering, developing, and delivering innovative medicines and healthcare solutions that improve patients' lives. They are heavily investing in AI and are building advanced Agentic AI solutions to accelerate scientific research and
We are looking for a highly skilled Senior Agentic AI Software Engineer with strong software engineering fundamentals and deep Python expertise. In this role, you will design and build Agentic AI systems that automate complex data and analysis workflows across multiple scientific domains. engineers, data scientists, and domain experts to turn high‐level research and business needs into robust, scalable, and production‐grade AI solutions.
Design, implement, and maintain Agentic AI solutions (LLM‐powered agents, tools, and workflows) for scientific and data‐intensive use cases.
● Build and support tools to orchestrate data processing, analysis, and decision‐making pipelines.
● Automate complex, multi‐step workflows using Python and modern AI/LLM frameworks.
● Integrate AI agents with internal systems and data sources via APIs, databases, and services.
● Ensure robustness, observability, and performance of Agentic AI systems in production.
● Apply software engineering best practices (testing, code review, CI/CD, documentation, monitoring).
● Design and develop MCP servers to connect and access internal data sources.
University degree in Computer Science, Engineering, Bioinformatics, or related field (M.Sc. or PhD is a plus).
● 5+ years of professional experience in software engineering, data engineering, data science, machine learning, or related areas.
● Strong, hands‐on Python programming skills (writing production‐grade code, libraries, and services).
Advanced RDBMS & Data Modeling: Expert-level SQL proficiency, including query optimization, indexing strategies, and handling complex relational schemas.
● Cloud Infrastructure (AWS Priority): Hands-on experience architecting and deploying Python applications in AWS (ECS, Lambda, S3, RDS) using Infrastructure as Code (IaC) principles.
● Software Engineering Excellence: Gitflow, unit/integration testing (PyTest), automated CI/CD pipelines, and conducting high-standard code reviews.
Practical experience with Retrieval-Augmented Generation, including vector database tuning (e.g.,LLM Lifecycle & Evaluation: Strong understanding of foundation model constraints, prompt engineering for production (DSPy/evaluation frameworks), and managing token latency/cost.
● Go, C++, or Rust) to handle performance-critical backend components or low-level optimizations.
● Data domain knowledge: Experience working with scientific data (Omics, Imaging, Clinical, Preclinical, etc..).