Senior Software Engineer, Seqera Labs

• Ideal candidates have strong backend experience, familiarity with cloud-native architectures (AWS/GCP), and are excited about applying AI to meaningful problems
• Bonus if you’ve worked with developer tools, scientific data, or deployed software in customer environments
• You’re a strong software engineer with experience across both backend and frontend systems
• You’ve built, shipped, and maintained real-world applications — ideally with exposure to data, ML, or research tooling
• You have production experience with at least one major cloud provider (AWS, GCP, Azure) and have built distributed systems or services using cloud-native patterns
• You’re comfortable with container technologies (Docker) and preferably orchestration tools like Kubernetes or Docker Compose
• You write well-tested, secure, and performant code and know how to balance speed with quality
• You’re independent, communicative, and thrive in fast-moving, collaborative teams
• You’re excited about AI and curious about scientific applications — and you want to work on real tools that help real scientists
• If you’re excited about this role and your past experience doesn’t align perfectly with every qualification in the job description, we encourage you to apply anyway. You may be just the right candidate for this or other roles

Desirable

• We’re looking for a senior software engineer to join our AI/Growth team and help us design and build AI-powered workflows, backend services, and user-facing tools that accelerate scientific discovery
• You’ll work with modern LLM frameworks, build robust APIs and services, and contribute to a team that balances experimentation with rock-solid engineering
• In this role, you’ll work across our stack — building AI-driven workflows, scalable backend services (Python), and user-facing tools (React). You’ll take ideas from concept to production, collaborating with a small, fast-moving team focused on delivering real value to real scientists
• Design and implement large language model (LLM)-driven workflows
• Build and maintain backend systems and APIs using Python and FastAPI
• Collaborate with frontend engineers on user-facing tools (React, Astro) that scientists love to use
• Own end-to-end services from development to deployment using cloud-native and containerized environments
• Improve our AI/Growth team’s engineering practices around testing, observability, automation, and release processes
• Partner closely with product, UX, and domain experts to understand how scientists use our tools — and how we can make them better