Principal Platform Software Engineer (Robotics and Lab Automation)

We are developing reusable software to integrate and coordinate diverse robots, scientific instruments, and laboratory equipment. These capabilities will enable reliable execution of physical tasks and capture of experimental data, helping scientists develop and operate intelligent, automated laboratories.

We are seeking a Principal Platform Software Engineer with deep experience in robotics software, process automation, and physical system integration. Working with scientists, product teams, hardware engineers, and AI specialists, you will translate emerging requirements and prototypes into reliable platforms, owning capabilities from design and implementation through deployment and operation.

This is a hands-on individual contributor role requiring strong software engineering skills and practical knowledge of robotic systems, equipment controllers, sensors, actuators, and their software interfaces. You will solve complex hardware and software integration challenges, guide technical decisions, and build reusable automation capabilities that accelerate scientific discovery. Practical experience applying AI—including tool use, context management, orchestration, and evaluation—will help you connect intelligent decision-making with dependable physical execution.

We welcome experience across scientific software, industrial automation, robotics, AI platforms, and related fields. Previous laboratory automation experience is valuable but is not essential.

This role requires working from Oracle’s London or Reading offices four days per week, with frequent travel to Oxford.

Responsibilities

Software Development and Platform Integration

• Personally design, implement, test, and deploy substantial platform capabilities, taking prototypes into supported production operation.

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

• Define modular service boundaries, shared interfaces, and reusable components across equipment integration, execution, orchestration, and data acquisition.

• Develop communications middleware and event-driven integrations with equipment, cloud services, and external platforms.

• Acquire instrument measurements, equipment telemetry, and execution metadata while preserving scientific context, provenance, and traceability.

• Automate equipment configuration, deployment, compatibility checks, diagnostics, testing, and routine operations.

• Lead code reviews and design discussions, document technical decisions, and contribute to engineering plans.

Customer-Focused Delivery

• Work with engineers, product managers, scientists, and research users to understand customer workflows, technical requirements, and operational constraints.

• Translate customer scenarios and feedback into actionable engineering tasks, acceptance criteria, and product improvements.

• Investigate customer issues and support rapid, iterative delivery while maintaining engineering quality.

• Develop an understanding of scientific workflows and identify opportunities to reuse capabilities across customers, instruments, and applications.

• Coordinate dependencies across software, hardware, infrastructure, data, and application teams.

Testing, Verification, and Physical Integration

• Build unit, integration, and functional tests; conduct performance, resilience, and system-level testing.

• Develop simulation and hardware-in-the-loop tests to validate equipment behavior, timing, repeatability, and fault recovery.

• Lead hands-on equipment integration, commissioning, calibration, and troubleshooting with hardware and controls specialists.

• Evaluate AI-assisted capabilities against defined acceptance criteria, including tool correctness, execution validation, and human oversight.

• Collaborate with safety and controls engineers to respect equipment interlocks, operating limits, fault containment, and safe failure behavior, preserving the independence of physical safety systems.

Reliability, Security, and Operations

• Support production services through an on-call rotation that provides 24×7 response coverage for service incidents.

• Add monitoring, logging, metrics, telemetry, health checks, and alerts to owned components.

• Investigate and resolve issues in development and production environments, including incident response, root-cause analysis, and corrective actions.

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

• Develop runbooks, support documentation, and automation for deployment, testing, recovery, and routine operations.

• Address service performance, equipment connectivity, version compatibility, and recovery from network or device failures.

Preferred Qualifications

• 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.

• Experience designing cloud-to-edge systems, distributed equipment management, or remote orchestration of physical automation.

• Experience with industrial or collaborative robotic arms, PLCs, motion controllers, mobile robots, or automated material-handling systems.

• Familiarity with robotics middleware and industrial communication technologies such as ROS 2, DDS, OPC UA, EtherCAT, Modbus, or vendor-specific robotics SDKs.

• Experience with robot calibration, kinematics, motion planning, machine vision, or coordinated multi-device operations.

• Experience integrating laboratory equipment such as liquid handlers, sample handlers, incubators, imaging systems, or analytical instruments.

• Familiarity with SiLA 2, laboratory information management systems (LIMS), workflow engines, scheduling, or shared-resource coordination.

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

• Exposure to AI/ML platforms, model training, model serving, retrieval-augmented generation (RAG), evaluation harnesses, AI agents, Model Context Protocol (MCP), or enterprise AI integrations.

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

• Experience developing shared platforms used by multiple teams or customers.

Previous laboratory automation experience is valuable but is not essential.

Location

Oracle’s London or Reading offices four days per week, with frequent travel to Oxford. This is a fully on-site role requiring hands-on laboratory integration, testing, commissioning, troubleshooting, and operational support.