Staff Software Engineer, Seqera Labs

• Deep experience building production-grade systems software, with technical ownership at Staff level
• Strong in Go and comfortable in C (or C++), close to the operating system
• Solid Linux internals — filesystems, namespaces, processes, signals, networking — and comfortable debugging at that level
• Built distributed and/or cloud-native systems and understand the failure modes of running across multiple clouds
• Write simple, well-structured, well-tested code; optimize for clarity and debuggability
• Comfortable with ambiguity and driving work independently
• We use AI every day and expect engineers to use it extensively — you don't need to be an expert, but you must be genuinely open to it

Desirable

• We are looking for a Staff Software Engineer to join our Unified Compute team and take technical ownership of the low-level systems that power how scientific workloads run in the cloud
• Our scheduling project (Sched) has gained real momentum, and we need a senior engineer to help build the ecosystem around it to the next level
• The core of this role is deep in the stack — Fusion (a FUSE filesystem presenting cloud object storage as POSIX), Fusion Snapshots (CRIU-based checkpoint/restore that survives spot-instance reclamation), and Ignite (a container process manager) — with Sched as the orchestration layer that ties compute together
• You'll also support adjacent services such as Groundswell (ML-based resource prediction) and Cloudinfo (multi-cloud pricing/metadata)
• It's a hands-on senior role with strong architectural influence
• Design, build, and own low-level systems across Fusion, Fusion Snapshots, Ignite, and Sched
• Write reliable, well-tested code primarily in Go and C, with Rust and JVM (Groovy/Java, Micronaut) where the codebase calls for it
• Work close to the OS: FUSE filesystems, Linux namespaces, CRIU checkpoint/restore, process supervision, signal handling, static musl builds
• Tackle multi-cloud orchestration and scheduling: provider abstractions (AWS, Azure, GCP), instance selection, autoscaling, spot-instance fault tolerance, durable async queues
• Drive performance engineering — chunked I/O, multi-level caching, buffer pools, bandwidth management
• Set technical direction and raise the standard for testing, observability, and operational excellence
• Mentor teammates and help onboard new engineers