SCiO is transforming material analysis by making it real-time, precise, and actionable. Our pocket-sized NIR spectroscopy solutions empower customers across food and agriculture to optimize operations, scale efficiently, and make confident, data-driven decisions. We build end-to-end cloud platforms that integrate hardware, data pipelines, analytics, and customer-facing applications, all operating at production scale.

We are now looking for a highly experienced, hands-on Backend Engineer who thrives in deep system work: designing reliable services, understanding system behavior in production, owning performance, scalability, observability, and data integrity, not just writing features.

This role is part of the Backend team within the Software department and has a direct impact on the core production platform.

What You’ll Do

• Design and implement backend services and APIs for a large-scale cloud platform.
• Own system-level responsibilities: performance, scalability, reliability, monitoring, and operational stability.
• Work on data-intensive pipelines, integrations, and distributed services.
• Participate in architecture design, technical decision-making, and long-term system evolution.
• Lead implementation from design through production deployment and ongoing maintenance.
• Troubleshoot production issues, perform root-cause analysis, and improve system robustness.
• Collaborate closely with product, algorithms, QA, DevOps, and embedded teams.

Who We’re Looking For

We are specifically looking for someone with real-world, production-grade backend experience, not only academic or feature-level development.

Must-Have

• 5+ years of hands-on Backend development on complex, production systems.
• Proven experience building and maintaining scalable, distributed services in production.
• Strong proficiency in Python (designing services, data processing, integrations).
• Experience working with at least one major cloud platform (AWS / GCP / Azure).
• B.Sc. in Computer Science / Engineering or equivalent practical experience.
• Strong ownership mindset and ability to work independently on complex systems.

Nice to Have

• Kubernetes / container orchestration in production environments.
• Experience with databases such as PostgreSQL, MongoDB, BigQuery.
• Experience designing APIs (REST / gRPC) and distributed systems.
• CI/CD pipelines and production deployment flows.
• Exposure to machine learning pipelines or data platforms.