We’re looking for hands-on engineers with expertise and passion in solving difficult problems in distributed systems, operating systems, virtualized infrastructure, and highly available services. If this is you, at Oracle you can design and build innovative new systems from the ground up. As our business grows, uptime for our cloud ecosystem is paramount. We engineer the real-time detection and repair of our distributed cloud infrastructure. You will work with engineers from all product areas within Oracle as we look to deliver next-generation cloud services.
Are you passionate about harnessing the power of Artificial Intelligence (AI) and Machine Learning (ML) to revolutionize cloud infrastructure and automation? Do you thrive in environments where no two days are ever the same, and creativity meets cutting-edge technology?
We're excited to meet a talented Senior Software Engineer like you, who shares our enthusiasm for innovation and excellence. As a valued member of our software engineering division in Seattle, you'll have the opportunity to shape the future of our technology stack and drive meaningful change in the world of cloud infrastructure and automation.
In this role, you'll design, develop, troubleshoot, and debug software programs for databases, applications, tools, networks, and other cloud infrastructure components. Your expertise in AI and ML will help us stay ahead of the curve, and your passion for collaboration will inspire our team to achieve greatness together.
If you're ready to unleash your full potential and make a lasting impact, we'd love to hear from you!
Location: Seattle, WA (there is no remote option for this role)
Internal Responsibilities
Key Responsibilities:
- Work independently in ambiguous situations to ensure adherence to published standards and practices.
- Design, develop, troubleshoot, and debug software programs for various cloud infrastructure components, including databases, applications, tools, and networks.
- Take an active role in defining and evolving standard practices and procedures for software engineering, with a focus on AI-driven development.
- Define and develop software for tasks associated with developing, designing, and debugging software applications or operating systems, leveraging AI and ML techniques.
- Lead the development of critical initiatives, including:
- Design and implement spike detection mechanisms for provisioning failures to minimize operational disruptions using ML algorithms.
- Expand integrations with Kafka to enable near real-time actions supporting 1-Day SLO objectives for hardware repairs, utilizing event-driven architecture and stream processing.
- Developing an automated ticket routing framework to streamline workflows, enhance efficiency, and reduce operational overhead, powered by NLP and ML.
- Accelerate dedicated initiatives through collaborative efforts with cross-functional teams and customers, applying AI-driven insights and recommendations.
- Harness the power of AI and ML to create innovative tools and frameworks that automate testing, simulate complex environments, and reproduce incidents, freeing up human ingenuity to focus on higher-value tasks and amplifying our ability to deliver exceptional customer experiences.
- Collaborate and lead technical discussions across multiple teams to ensure seamless integrations and effective problem-solving.
- Provide direction and mentoring to junior engineers, sharing knowledge and expertise to promote growth and development.
Technical Skills:
- Programming languages: Python, Java, TypeScript
- Messaging platforms: Kafka
- Development methodologies: Agile Principles
- User Experience (UX) design principles
- Data management: data modeling, data warehousing, data governance
- Cloud infrastructure: OCI, AWS, Azure, Google Cloud Platform (GCP)
- Operating Systems: Linux, MacOS
- Scripting languages: Bash, Perl, Ruby
- Familiarity with containerization technologies such as Docker
- API design and development: RESTful APIs, API gateways, API security
- Familiarity with API documentation tools such as Swagger/OpenAPI
- AI and ML frameworks: TensorFlow, PyTorch, Keras, scikit-learn
- NLP libraries: NLTK, spaCy
- Experience with AI-powered tools and platforms: chatbots, virtual assistants, predictive analytics
External Responsibilities
Key Responsibilities:
- Work independently in ambiguous situations to ensure adherence to published standards and practices.
- Design, develop, troubleshoot, and debug software programs for various cloud infrastructure components, including databases, applications, tools, and networks.
- Take an active role in defining and evolving standard practices and procedures for software engineering, with a focus on AI-driven development.
- Define and develop software for tasks associated with developing, designing, and debugging software applications or operating systems, leveraging AI and ML techniques.
- Lead the development of critical initiatives, including:
- Design and implement spike detection mechanisms for provisioning failures to minimize operational disruptions using ML algorithms.
- Expand integrations with Kafka to enable near real-time actions supporting 1-Day SLO objectives for hardware repairs, utilizing event-driven architecture and stream processing.
- Developing an automated ticket routing framework to streamline workflows, enhance efficiency, and reduce operational overhead, powered by NLP and ML.
- Accelerate dedicated initiatives through collaborative efforts with cross-functional teams and customers, applying AI-driven insights and recommendations.
- Harness the power of AI and ML to create innovative tools and frameworks that automate testing, simulate complex environments, and reproduce incidents, freeing up human ingenuity to focus on higher-value tasks and amplifying our ability to deliver exceptional customer experiences.
- Collaborate and lead technical discussions across multiple teams to ensure seamless integrations and effective problem-solving.
- Provide direction and mentoring to junior engineers, sharing knowledge and expertise to promote growth and development.
Technical Skills:
- Programming languages: Python, Java, TypeScript
- Messaging platforms: Kafka
- Development methodologies: Agile Principles
- User Experience (UX) design principles
- Data management: data modeling, data warehousing, data governance
- Cloud infrastructure: OCI, AWS, Azure, Google Cloud Platform (GCP)
- Operating Systems: Linux, MacOS
- Scripting languages: Bash, Perl, Ruby
- Familiarity with containerization technologies such as Docker
- API design and development: RESTful APIs, API gateways, API security
- Familiarity with API documentation tools such as Swagger/OpenAPI
- AI and ML frameworks: TensorFlow, PyTorch, Keras, scikit-learn
- NLP libraries: NLTK, spaCy
- Experience with AI-powered tools and platforms: chatbots, virtual assistants, predictive analytics
