Senior Software Engineer

• 4+ years building and operating production backend services, with real ownership of at least one.

• Strong in Java and/or Groovy, with Micronaut, Spring Boot or similar.

• Real hands-on experience with a major cloud provider's API - provisioning and managing resources programmatically, not just deploying to it.

• Have worked with Kubernetes as somewhere workloads actually run.

• You care about correctness. Ideally you have worked on billing, metering or other systems where wrong data has consequences - and if not, you bring the same rigour to data integrity anyway.

• Comfortable designing REST APIs and data models, and keeping integrations working across versions and failures.

• Have been accountable for something customer-facing in production.

• Comfortable inheriting a system, asking questions, and writing down what was never documented.

• Comfortable with ambiguity - you develop hypotheses with limited information, drive work independently, and reach out early to stay unblocked.

• We use AI every day and expect engineers to use it extensively. You do not need to be an expert, but you must be genuinely open to it.

• Multiple clouds - hands-on across two or more of AWS, Azure, GCP.

• HPC and batch schedulers (Slurm, LSF, PBS, AWS Batch, Google Batch, Azure Batch).

• GPU workloads and GPU-enabled provisioning.

• Usage-based billing or monetization platforms (Metronome, Stripe) and pay-as-you-go pricing.

• Self-serve or free-tier product work: signup funnels, usage limits, conversion.

• Bioinformatics, Nextflow, or scientific computing background.

• Observability tooling (Prometheus, Grafana, ELK) and CI/CD ownership.

• Some frontend exposure (Angular).

• Open-source contributions

We are looking for a Senior Software Engineer to join our Unified Compute team and take ownership of the application layer that turns computational capability into something our customers can configure, run, and pay for - spanning Seqera Intelligent Compute, its integration with the Seqera Platform, and the metering and billing that sits behind them. This layer is essential to our customer-facing platform's operational success: it determines whether biotech innovators and researchers can set up the compute they need, run their workloads reliably wherever they run them, and see transparent, accurate insight into what they used and what it cost.

You will help shape a backend that supports compute environment provisioning across AWS, Azure, GCP, Kubernetes, HPC schedulers and GPU executions; multi-tenant usage tracking and accurate billing computation across cloud and on-prem deployments; and the pay-as-you-go and free-tier onboarding journeys that bring new users onto the platform. The role spans high-impact engineering work - from system architecture design to data modeling, cloud provider integrations, and API development - using JVM technologies (Java, Groovy, Micronaut).

You will be empowered to influence our architecture decisions, improve the lifecycle of compute provisioning and billing processes, and collaborate closely with product, platform, and infrastructure teams to deliver world-class engineering outcomes. It is a broad scope, and you will own it end to end, with three engineers alongside you in the team to lean on for the hardest calls.

• Build and own the integration between Seqera Intelligent Compute and the Seqera Platform.

• Own Platform compute environments: let customers set up and run compute across AWS, Azure and GCP, Kubernetes, HPC schedulers, and GPU-enabled executions - and handle the ways those backends differ.

• Build against cloud provider APIs and SDKs, and handle what the real world returns: partial failures, quota and permission errors, provider quirks that leak into the product.

• Own the billing and pay-as-you-go path - metering usage accurately, keeping usage events and invoices reconcilable, and making the free-user onboarding journey work.

• Design data models and APIs that stay consistent across services and releases.

• Make failures legible: turn raw provider and scheduler errors into something a user can act on, and add the tests and observability that make the next incident faster to diagnose.

• Work directly with the Platform and product teams, and with support on escalations from real customers.

• Take design decisions within your scope and document the system so it is not dependent on any one person.