Lead Principal Platform Software Engineer

Oracle • Nashville, TN

1d • Onsite

About The Position

Oracle’s AI and Robotics team is building software platforms that connect scientific workflows, AI, robotics, and laboratory automation for the Ellison Institute of Technology. Within Oracle Cloud Infrastructure, the team develops shared cloud services, integration frameworks, execution infrastructure, and developer tools for AI-enabled life sciences laboratories. These capabilities support scientists and application teams in developing and operating automated workflows across robots, scientific instruments, and laboratory equipment.

The Lead Principal Software Engineer will set long-term technical direction for the Robotics Automation Platform and lead architecture and technical delivery across services and teams. This hands-on individual contributor role combines architectural leadership with substantial implementation work: guiding principal and senior engineers, building foundational capabilities, and resolving complex issues across distributed services, AI infrastructure, and equipment integration. The position is based fully on-site in Oracle’s Nashville office, with close collaboration with engineering teams in the United Kingdom and India Development Centre. UK colleagues will support physical equipment integration and laboratory validation, working with the role on platform interfaces, simulation, diagnostics, and system verification. Previous laboratory automation experience is valuable but not essential.

The role owns the technical architecture and evolution of shared platform capabilities spanning cloud services, execution infrastructure, equipment integration, and developer tooling. It includes defining service boundaries, APIs, equipment models, secure interfaces, execution and recovery patterns, AI-agent infrastructure, and clear boundaries between AI decisions, deterministic execution, equipment control, and independent physical safety systems. The engineer will personally design, implement, test, and deploy critical components; partner with product leaders, scientists, customers, and engineers to shape roadmaps and delivery; mentor experienced engineers; and establish consistent engineering practices.

The position also leads verification, system integration, reliability, security, and operations. Responsibilities include defining testing and evaluation strategies, simulation and hardware-in-the-loop frameworks, operational objectives, secure development patterns, observability standards, deployment automation, and incident response. Production support includes participation in an on-call rotation providing 24×7 response coverage for service incidents.

Requirements

• At least 8 years of professional software engineering experience, including sustained technical leadership for complex production platforms or distributed systems.
• Demonstrated architectural ownership across multiple services and teams, from ambiguous requirements through deployment and ongoing operation.
• Deep expertise in cloud-native distributed systems, service design, APIs, and integration frameworks.
• Strong, current programming skills in Python, Go, Java, C++, or similar languages, with evidence of personally delivering substantial production software.
• Experience building infrastructure for agentic systems, including tool integration, context and state management, orchestration, evaluation, human review, and failure recovery.
• Strong understanding of concurrency, asynchronous execution, message delivery, persistence, consistency, and recovery across distributed components.
• Experience defining secure interfaces, data models, service contracts, and engineering standards that allow teams to deliver compatible capabilities independently.
• Ability to resolve complex technical trade-offs across reliability, security, scalability, performance, cost, and delivery priorities.
• Proven ability to influence cross-team decisions, mentor experienced engineers, and communicate technical strategy to technical and non-technical stakeholders.
• Experience collaborating across geographically distributed teams, with clear technical documentation and effective asynchronous communication.
• Bachelor’s degree in computer science, Robotics, Engineering, or a related discipline, or equivalent practical experience.

Nice To Haves

• Experience with OCI, AWS, Azure, Google Cloud, or another cloud platform.
• Deep experience with Kubernetes, Docker, microservices, distributed data systems, event-driven architectures, or workflow orchestration.
• Experience designing cloud-to-edge platforms, remote equipment management, or distributed orchestration of physical systems.
• Experience with robotics or industrial integration technologies such as ROS 2, DDS, MQTT, OPC UA, or vendor equipment SDKs.
• Experience with laboratory software platforms, electronic laboratory notebooks (ELN), laboratory information management systems (LIMS), SiLA 2, or instrument integration frameworks.
• Experience building simulation, hardware-in-the-loop testing, or evaluation infrastructure for robotics or AI-enabled systems.
• Experience with workflow engines, scheduling, planning, or shared-resource coordination.
• Experience with data engineering, scientific data pipelines, metadata management, data provenance, or data governance.
• Experience with 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 evolving customer pilots into extensible platform offerings and driving adoption across multiple teams or customers.
• Laboratory automation experience.

Responsibilities

• Own the technical architecture and evolution of shared platform capabilities across cloud services, execution infrastructure, equipment integration, and developer tooling.
• Define modular architectures, versioned APIs, typed interfaces, compatibility expectations, and reference implementations.
• Build critical services and resolve difficult implementation, integration, and performance problems.
• Establish patterns for event-driven communication, equipment state representation, command execution, and recovery without unintended repetition of physical actions.
• Define scientific data-ingestion and metadata interfaces that preserve experimental context, provenance, and traceability.
• Lead cross-team design and code reviews, document decisions, and ensure implementations are clean, maintainable, secure, and well tested.
• Establish AI-assisted development practices supported by rigorous review, testing, and validation.
• Partner with product managers, scientists, customers, and engineering leaders to understand workflows, constraints, and strategic requirements.
• Translate customer scenarios into platform capabilities, technical roadmaps, acceptance criteria, and achievable delivery increments.
• Validate architectural assumptions through prototypes, customer feedback, and operational evidence.
• Guide the transition from pilot integrations to reusable capabilities supporting multiple laboratories, vendors, applications, and customers.
• Coordinate technical dependencies and integration milestones across UK, IDC, and US teams; enable rapid iteration while maintaining engineering quality and clear ownership across service boundaries.
• Define verification strategies spanning unit, integration, functional, performance, resilience, and system-level testing.
• Establish simulation, equipment emulation, and hardware-in-the-loop integration frameworks with UK-based engineers responsible for physical laboratory testing.
• Define acceptance criteria for equipment interfaces, execution semantics, fault recovery, and compatibility.
• Establish evaluation infrastructure for AI-enabled capabilities, including tool correctness, context handling, execution validation, and human approval.
• Ensure platform designs respect equipment operating limits, interlocks, and safety boundaries defined by controls and safety specialists.
• Lead investigations into failures spanning cloud services, communications, local execution, and equipment interfaces.
• Define service objectives and operational readiness expectations for availability, latency, resilience, capacity, and recovery.
• Establish identity, access control, policy enforcement, secure communications, auditability, and data protection patterns.
• Support production services through an on-call rotation providing 24×7 response coverage for service incidents.
• Define observability standards for monitoring, logging, metrics, telemetry, health checks, and alerts.
• Lead complex incident investigations, root-cause analysis, and corrective actions across service and team boundaries.
• Follow OCI standards for secure development, reliability, availability, privacy, and operational readiness.
• Establish deployment automation, runbooks, support documentation, compatibility management, and recovery procedures.
• Mentor principal and senior engineers and establish consistent engineering practices across the platform.

Benefits

• Medical, dental, and vision insurance, including expert medical opinion.
• Short-term and long-term disability insurance.
• Life insurance and AD&D.
• Supplemental life insurance for employees and eligible family members.
• Health care and dependent care Flexible Spending Accounts.
• Pre-tax commuter and parking benefits.
• 401(k) Savings and Investment Plan with company match.
• Flexible or accrued vacation, depending on employee eligibility and position classification.
• 11 paid holidays.
• Paid sick leave: 72 hours upon hire, refreshing each calendar year, with unused hours carrying over up to a 112-hour cap.
• Paid parental leave.
• Adoption assistance.
• Employee Stock Purchase Plan.
• Financial planning and group legal benefits.
• Voluntary auto, homeowner, and pet insurance.
• May be eligible for bonus, equity, and compensation deferral.

What This Job Offers

• Job Type: Full-time
• Career Level: Principal