We are seeking an experienced Senior Principal Software Engineer with a robust background in backend engineering, AI/ML, and large-scale cloud systems, to lead the implementation team for next-generation Infrastructure / AI / MLOps solutions. You will play a key role in ensuring the reliability, performance, and scalability of modern cloud-based AI applications for OCI Operations. This position involves close collaboration with development, operations, and security teams to automate processes, develop SRE standards, monitor system health, and maintain optimal uptime for critical AI applications. You will leverage your technical expertise to design, automate, and maintain AI services supporting mission-critical AI and ML initiatives.

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Career Level - IC4

In this role, you will:

Design and implement comprehensive automation pipelines for infrastructure, security, and compliance, enabling seamless policy enforcement throughout the product lifecycle.
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, implement and optimize large-scale analytics pipelines and underlying infrastructure on top of large Relational and Non-Relational data stores striking right balance between consistency, availability, and performance.
Architect concurrent, multi-region topologies on OCI, designing and deploying service stacks across two or more regions to ensure high availability and optimal performance.
Build production-grade MLOps workflows leveraging internal OCI tools and platform (OCI Data Science, Data Integration Service etc.) enabling 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.
Design, implement, and maintain scalable, secure cloud infrastructure for AI Applications on OCI
Collaborate with Engineering teams to build robust automation to build, deploy, and scale resilient systems
Identify opportunities and take ownership of automation and/or continuous improvement opportunities to run highly scalable reliable systems
Design and optimize highly available services that are resilient to failures or impacts
Automate infrastructure provisioning and CI/CD deployments with tools like Terraform, Ansible, or other IAC frameworks
Instrument and monitor components for performance, availability, resource consumption, and latency using observability tools (e.g., Grafana, Prometheus)
Troubleshoot and resolve complex issues, conducting root cause analyses and post-incident reviews
Solve complex problems related to infrastructure cloud services and automate common tasks to ensure continuous availability with minimal human intervention.
Utilize a deep understanding of cloud computing design patterns and their dependencies to mitigate complex major incidents.
Advocate for and implement security, governance, and compliance best practices
Mentor team members and promote knowledge sharing around SRE practices and Standards

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, data and infrastructure systems , backend engineering, DevOps, or ML Ops roles.
Extensive programming and coding expertise in Java/Python/Scala, with a proven track record of delivering production-quality solutions.
Deep hands-on expertise with a major cloud platform (OCI, AWS, GCP, Azure), 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).
Solid 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).
Good knowledge of RDBMS, Query optimization and NoSQL data stores.
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.
Experience in progressive rollout strategies and driving the technical vision for AI-powered analytics solutions.
Proven ability to drill into code, resolve complex technical challenges, and actively contribute to problem resolution in high-impact projects.
Effective communication and collaboration skills, with the ability to mentor others while remaining involved in implementation activities.
Demonstrated experience operating and optimizing large-scale analytics workloads (Spark/Data Flow, Autonomous Data Warehouse, Object Storage).