Senior Platform Software Engineer (Robotics and Lab Automation)

Responsibilities

Software Development and Platform Integration

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

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

• Build reusable device interfaces, APIs, execution components, and workflow integrations.

• Implement communications between equipment, local services, cloud platforms, and external systems.

• Capture instrument measurements, equipment telemetry, and execution metadata while preserving experimental context and traceability.

• Maintain configuration records, compatibility checks, diagnostics, and deployment scripts.

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

Customer-Focused Delivery

• Work with engineers, product managers, scientists, and laboratory users to understand workflows, requirements, and feedback.

• Help translate customer scenarios into actionable engineering tasks, acceptance criteria, and product improvements.

• Investigate customer feedback, troubleshoot issues, and contribute to rapid iteration while maintaining engineering quality.

• Learn the scientific and technical domain and identify opportunities to reuse solutions across instruments, workflows, and customers.

• Communicate progress, blockers, and integration dependencies to the team.

Testing, Verification, and Physical Integration

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

• Develop simulation and hardware-in-the-loop tests with guidance from experienced engineers.

• Help verify equipment timing, repeatability, reliability, and recovery under fault conditions.

• Support physical integration, commissioning, calibration, and fault-finding alongside hardware and controls specialists.

• Test AI-assisted integrations against defined acceptance criteria, including tool behaviour, execution validation, and human oversight.

• Implement agreed operational checks, fault responses, and operator controls with safety and controls specialists, respecting 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, contributing to incident investigation, root-cause analysis, and corrective actions.

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

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

• Help diagnose equipment connectivity, configuration, version compatibility, and service performance issues.

Preferred Qualifications

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

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

• Exposure to cloud-to-edge deployments, remote equipment management, or distributed automation systems.

• Experience with industrial or collaborative robots, motion controllers, PLC interfaces, sensors, or automated material-handling systems.

• Experience integration imaging system or robotic using vendor APIs, ROS 2, DDS, OPC UA, EtherCAT, Modbus, or vendor robotics SDKs.

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

• Exposure to machine vision, robot calibration, motion planning, simulation, or hardware-in-the-loop testing.

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

• Exposure to data engineering, 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.

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.