At Oracle Cloud Infrastructure (OCI), we are shaping the future of enterprise cloud with a diverse team of innovators committed to excellence. Blending the agility of a start-up with the global reach of the world’s leading enterprise software company, we empower our teams to create breakthrough solutions and deliver value to our customers.

Our team (OCI Horizon Data Science & Analytics team) is mainly focused on developing advanced analytics, machine learning, and generative AI-powered solutions and applications that provide actionable insights and drive impactful decision making across OCI, including finance, products, operations, support, and more.

We are seeking a highly experienced and passionate Senior Principal Software Developer with a strong background in backend development, machine learning, and AI/GenAI, to play a leading role in the design, development, and deployment of next-generation AI-driven analytics solutions. In this key role, you will collaborate with cross-functional teams, architect and implement robust backend systems, and help bring innovative GenAI analytics capabilities to Oracle Cloud customers. Your expertise will ensure the security, scalability, and performance of our systems, driving forward OCI’s mission to deliver intelligent cloud experiences.

We are seeking an experienced Senior Principal Software Developer with a robust background in backend engineering, AI/ML, and large-scale cloud systems, to lead the development of next-generation GenAI analytics solutions. In this role, you will:

Architect concurrent, multi-region topologies on OCI, designing and deploying service stacks across two or more regions to ensure high availability and optimal performance. Design and implement comprehensive automation pipelines for infrastructure, security, and compliance, enabling seamless policy enforcement throughout the product lifecycle. Operate and optimize large-scale analytics workloads using Spark/Data Flow, Autonomous Data Warehouse, and Object Storage, driving enhanced performance and efficiency. Build production-grade MLOps workflows leveraging OCI Data Science, Data Integration Service, and related analytics tools—including reproducible training pipelines, model fine-tuning and registry, and CI/CD-based deployment strategies (Functions or OKE) with progressive rollout capabilities.

This is a highly impactful role where you will collaborate cross-functionally, shape critical backend and ML architecture decisions, and drive innovation in AI-powered analytics on the Oracle Cloud. If you thrive on big challenges and want to help define the future of cloud intelligence, we’d love to meet you.

Basic Qualifications 

Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field. Minimum 10 years of hands-on software engineering experience, including direct responsibility for designing, building, and operating large-scale backend and infrastructure systems. Extensive coding expertise in Python and Java, with a proven track record of delivering production-quality solutions. Deep hands-on expertise with a major cloud platform (Oracle Cloud Infrastructure preferred), and proficiency with containerization technologies (Docker, Kubernetes). Demonstrated experience architecting, implementing, and operating secure, scalable, and highly available cloud-based infrastructures (Oracle Cloud Infrastructure preferred). Direct, practical experience deploying and optimizing CI/CD pipelines, automation tools, and infrastructure as code (e.g., Terraform, Ansible). Deep understanding of DevOps/ML Ops practices, including hands-on involvement in building, deploying, and managing analytics/ML models in production. Proven ability to design, evolve, and maintain RESTful APIs (OpenAPI/Swagger). Advanced knowledge of SQL (schema design, query optimization) and NoSQL fundamentals (e.g., Redis). Proven ability to drill into code, resolve complex technical challenges, and actively contribute to problem resolution in high-impact projects. Strong communication and collaboration skills, with the ability to mentor others while remaining involved in implementation activities

Preferred Qualifications 

Master’s or higher degree in Computer Science or a related field. 12+ years of professional experience in cloud infrastructure, backend engineering, DevOps, or ML Ops roles. Recognized certifications in cloud computing, security, or DevOps methodology. Demonstrated experience operating and optimizing large-scale analytics workloads (Spark/Data Flow, Autonomous Data Warehouse, Object Storage). Track record of building production-grade MLOps workflows and deploying ML/AI models at scale. Experience designing secure, automated, and compliant infrastructure in regulated environments. Advanced coding skills in Python and Java, plus experience with distributed computing frameworks (Spark, Hive). Prior roles supporting major production systems, operations, cloud support, or similar high-availability domains. Strong knowledge of cloud platform (AWS, OCI, Azure) architectures and operational best practices. Deep understanding of data structures, algorithms, and software engineering best practices. Experience in progressive rollout strategies and driving the technical vision for AI-powered analytics solutions.