8+ years of experience
About the opportunity
We are looking for a Senior Software Engineer to join an AI Engineering team within a global organization building data platforms and AI-powered capabilities for research, healthcare, and life sciences.
The role focuses on developing scalable and reusable generative AI services and platform capabilities, combining software architecture, backend engineering, distributed systems, and AI integration in production environments.
You will have an important role in shaping technical solutions across multiple services, helping transform AI prototypes into robust, production-ready capabilities.
What you will be working on
- Lead architectural design and help ensure technical consistency across services.
- Design and develop reusable generative AI services and components.
- Transform AI prototypes into scalable, production-ready systems.
- Contribute to system design across multiple services and modules.
- Define and promote engineering best practices around scalability, observability, CI/CD, and testing.
- Build and deploy scalable applications in Kubernetes environments.
- Collaborate with product, platform, and research teams.
- Mentor engineers and contribute to engineering standards and practices.
- Participate in code reviews, architecture discussions, and cross-team technical initiatives.
- Stay up to date with developments in generative AI and support their responsible adoption.
Technical background
We are looking for strong experience with:
- Python
- Java
- Kubernetes / EKS
- Cloud-native architectures
- Backend systems and API development
- AI / LLM tooling, such as LangChain and LangGraph
- Data modeling
- Distributed systems
The profile we are looking for
- Senior software engineer with strong platform and architecture experience.
- Strong backend engineering and AI integration knowledge.
- Experience designing and building scalable distributed systems.
- Experience mentoring engineers and collaborating across multiple teams.
Nice to have
- Experience building internal AI platforms.
- Experience with observability, including metrics, logging, and alerts.
- Knowledge of knowledge graphs or semantic search systems
