Principal Platform Software Engineer

What You’ll Do

• Design, develop, test, and maintain software components for cloud platform services.

• Implement backend services, APIs, data-ingestion and processing components, workflow integrations, automation, and operational tooling.

• Work with other engineers and product managers to understand requirements and translate customer scenarios into well-defined software features.

• Contribute to rapid iteration by investigating customer feedback, troubleshooting issues, and improving product functionality.

• Write clean, maintainable, secure, and well-tested code using established OCI engineering practices.

• Build unit, integration, and functional tests; participate in performance and resilience testing.

• Add logging, metrics, telemetry, health checks, and alerts to improve service observability.

• Help investigate, debug, and resolve service issues in development and production environments.

• Participate in code reviews, design discussions, documentation, and engineering-planning activities.

• Automate repeatable tasks related to deployment, configuration, testing, and service operations.

What You’ll Bring

• 10+ years of professional software development experience, including experience delivering production software or services.

• Domain awareness of bioinformatics or computational life sciences, such as genetics, genomics, plant biology, or generative biology.

• Understanding of scientific computing workflows and the challenges associated with large datasets, reproducibility, metadata, provenance, and compute resource requirements

• Strong programming skills in one or more languages such as Java, Go, or Python.

• Experience developing backend applications, cloud-native services, distributed-system components, data-processing applications, or workflow systems.

• Ability to independently deliver well-scoped features and components, with guidance on broader technical design and prioritization.

• Experience working collaboratively in an Agile or iterative software development environment.

• Curiosity and willingness to learn rapidly from customers, product managers, applied scientists, and senior engineers.

• Familiarity with REST APIs, source control, code review, automated testing, CI/CD, containers, and cloud services.

• Bachelor’s degree in computer science, engineering, or a related field, or equivalent practical experience.

Responsibilities

Software Development

• Implement features and services from defined requirements and technical designs.

• Develop maintainable code, APIs, data-processing components, integrations, and automated tests.

• Debug defects and improve the performance, reliability, and usability of owned components.

• Participate in code reviews and apply feedback to improve technical quality.

Customer-Focused Delivery

• Support the team in understanding customer workflows, technical requirements, and feedback.

• Help translate feedback into actionable engineering tasks and product improvements.

• Contribute to fast, iterative delivery while maintaining engineering discipline and quality.

• Learn the scientific and technical domain and identify opportunities to make solutions reusable across customers.

Reliability, Security, and Operations

• Support production services as part of an on-call rotation assuring 24x7 response to service incidents.

• Add monitoring, logging, and telemetry to owned components.

• Assist with service troubleshooting, incident investigation, and root-cause analysis.

• Follow secure-development practices and OCI standards for reliability, availability, privacy, and operational readiness.

• Contribute to runbooks, support documentation, and automation for deployments, testing, and routine operations.

Preferred Qualifications

• Knowledge of high-performance computing, Linux environments, batch scheduling, and resource management, particularly Slurm.

• Experience supporting scientific pipelines that use CPU or GPU compute, shared or parallel storage, and large-scale data movement.

• Experience with Nextflow and the Seqera platform, or other established scientific workflow systems such as Snakemake, Cromwell/WDL, or CWL-based platforms

• Familiarity with common biological data formats, analysis pipelines, and the operational needs of research users.

• Experience with OCI, AWS, Azure, Google Cloud, or another cloud platform.

• Experience with Kubernetes, Docker, microservices, distributed data systems, event-driven architecture, or workflow orchestration.

• Exposure to data engineering, data platforms, scientific data, data pipelines, metadata management, or data governance.

• Exposure to AI/ML platforms, model training, model-serving systems, RAG, evaluation harnesses, AI agents, MCP, or enterprise AI integrations.

• Experience supporting scientific, research, life-sciences, or enterprise platform workloads.