Oracle is seeking a Principal Software Developer to help design and build an AI-powered Digital Twin platform. The platform will combine real-time operational data, digital models, simulation, graph technologies, and AI agents to help customers understand complex systems, predict outcomes, investigate issues, and automate actions safely.

This is a senior individual contributor role for an engineer who can lead complex technical initiatives, influence architecture across teams, and deliver production-grade capabilities spanning distributed systems, data platforms, generative AI, and agentic workflows.

Responsibilities

• Design and build scalable services for digital models, telemetry, state management, relationships, simulation, and real-time analytics.
• Develop AI agents that reason over digital twin data, enterprise knowledge, telemetry, and operational systems.
• Build capabilities for RAG, graph-based retrieval, agent orchestration, tool use, memory, evaluation, and human approval.
• Define technical designs and influence architecture across multiple components and engineering teams.
• Develop secure, reliable, and observable distributed systems for enterprise cloud environments.
• Ensure AI-generated recommendations and actions are grounded, explainable, auditable, and policy-compliant.
• Partner with product managers, applied scientists, architects, and engineers to convert customer requirements into scalable platform capabilities.
• Lead complex feature development from design through implementation, testing, deployment, and production support.
• Improve engineering quality through design reviews, code reviews, automated testing, operational readiness, and technical mentoring.
Investigate and resolve difficult performance, reliability, data consistency, and production issues.

Qualifications

• 8+ years of software engineering experience building large-scale production systems.
• Strong programming skills in Java, Python, Go, C++, or a comparable language.
• Deep understanding of distributed systems, data structures, algorithms, APIs, databases, and cloud architecture.
• Experience designing and operating highly available, multi-tenant cloud services.
• Experience with generative AI, large language models, RAG, AI agents, or agentic orchestration.
• Familiarity with graph databases, vector search, event streaming, time-series data, or simulation systems.
• Experience delivering complex projects across multiple services or teams.
• Strong debugging, problem-solving, and system-design skills.
Ability to communicate technical decisions clearly and influence without direct authority.

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Preferred Qualifications

• Experience with digital twins, IoT, industrial systems, cloud operations, or simulation platforms.
• Experience with LangGraph, LangChain, LlamaIndex, Semantic Kernel, OCI Generative AI Agents, or similar technologies.
• Knowledge of LLMOps, agent evaluation, prompt and policy versioning, model monitoring, and AI governance.
• Experience building knowledge graphs, hybrid retrieval systems, or enterprise RAG solutions.
• Experience applying AI agents to root-cause analysis, predictive maintenance, optimization, incident response, or automated remediation.
• Experience with OCI, Oracle Database, Kubernetes, graph databases, streaming platforms, or vector databases.
Experience mentoring engineers and providing technical leadership for major platform initiatives.

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Key Responsibilities
System Design & Architecture - System Scalability:
–Lead the development and implementation, and begin to architect, components of scalable distributed systems that support horizontal and vertical scaling to meet system demands, including leveraging distributed state management tools.
–Optimize code and/or systems for large-scale data processing and high-throughput requirements to support hyper-scale systems.
–Define scalability requirements for owned components and ensure design and implementation requirements are met.
–Design systems to scale with elasticity (e.g., effectively scaling both up and down).
–Leverage data plane platforms to effectively handle large-scale data retrieval, storage, and processing.
–Design performance and load testing.

System Design & Architecture - System Reliability Design:
–Build and design fault-tolerant components and systems capable of withstanding in-service updates by implementing redundancy, replication, and automatic failover mechanisms.
–Design systems to effectively handle service disruptions (e.g., network partitions) by prioritizing consistency, availability, or partition tolerance.
–Implement and optimize approaches to handle network unreliability, including load-shedding, throttling, and rate-limiting.
–Design components and systems that are durable and adhere to service level objectives (SLOs), setting expectations for availability and durability of other computing services within the department.

System Design & Architecture - System Reliability Performance:
–Define key performance indicators (KPIs) and telemetry to identify gaps or issues in running systems.
–Build and customize moderately complex dashboards, telemetry systems, and alerting mechanisms to proactively monitor components and system health.

System Design & Architecture - Correctness / Availability:
–Design and implement functional and correctness requirements for feature sets and/or systems in new or existing systems.
–Design complex test scenarios (e.g., fault-injection, brown-out) to evaluate system correctness.
–Implement data replication and synchronization techniques to maintain data integrity and availability.

Operational Troubleshooting & Incident Management:
–Take a proactive role in diagnosing, debugging, and resolving issues in active components and systems to support ongoing operation, and mentor others in these processes.
–Implement strategies to prevent interruptions, ensuring no maintenance windows are required for customers and users when resolving issues.
–Maintain expertise in owned components and systems to ensure effective troubleshooting and performance.
–Meet operational readiness expectations through design and implementation.
–Serve in operational support rotations, providing guidance in incident response and root cause investigations.

Compliance & Security:
–Implement robust security measures to protect data and applications in multi-tenant environments, including encryption techniques and access controls.
–Execute remediation plans to address identified security gaps.
–Ensure cloud infrastructure is in compliance with industry standards and regulations and that documentation is up to date.

Automation & Change Management:
–Develop and maintain automation scripts and tools (e.g., Infrastructure as Code (IaC)) to manage cloud infrastructure.
–Create and adhere to change management plans for patching, updating, and rolling back applications, and begin designing systems and components to allow for automation of these processes.

Core Responsibilities
Planning & Execution:
–Manages and coordinates moderately complex tasks, monitoring timelines and deliverables to ensure timely completion and adherence to requirements for a moderately-sized project or initiative. Efficiently delegates, monitors, and prioritizes work across multiple projects, providing technical oversight and adjusting plans to address shifts in resources or timelines.
Collaboration & Partnership:
–Collaborates across the organization to align on expectations and achieve shared objectives. Leverages understanding of business leaders, stakeholders, and/or customers to ensure proposed solutions meet their needs. Supports inclusivity by actively seeking and listening to diverse perspectives, ensuring others feel heard and respected.

Problem Solving:
–Identifies and addresses moderately complex issues by analyzing a wide range of data and/or information to identify solutions in accordance with standard practices. Proactively escalates unresolved or critical issues with a thorough assessment and suggests potential solutions. Reviews, contributes to, and documents problem solving strategies.

Continuous Learning:
–Pursues learning opportunities to expand knowledge and skills and/or tools in new areas and stays abreast of the latest industry trends and best practices. Proactively seeks and leverages ongoing feedback and training to improve skills. Coaches and mentors junior team members, fostering continuous learning and knowledge sharing within and across teams.

Continuous Improvement:
–Develops ideas, recommends updates, and/or collaborates on the implementation of process improvements to increase the efficiency and effectiveness of processes, protocols, and workflows across teams, and evaluates the impact on key stakeholders. Solicits feedback from others on ideas for alternative approaches and methods for continued improvement.

Performance and Development:
–Contributes to the talent development pipeline by participating in candidate interviews, assessing candidates, and providing hiring recommendations.