Senior Platform Software Engineer

You will develop production-quality components while building depth in cloud platforms, distributed data systems, scientific workflows, and AI-enabled services. You will combine strong software engineering skills with a practical understanding of bioinformatics or computational science across areas such as genomics, plant biology, or generative biology. You are expected to work at Oracle’s London or Reading offices 4 days a week for this role. The role will also require you to frequently travel to Oxford. 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  3+ 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 architectures, 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.