IBM
Software Engineer - Cloud Compute Platform
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Introduction
At IBM Software, we transform client challenges into solutions. Building the world’s leading AI-powered, cloud-native products that shape the future of business and society. Our legacy of innovation creates endless opportunities for IBMers to learn, grow, and make an impact on a global scale. Working in Software means joining a team fueled by curiosity and collaboration. You’ll work with diverse technologies, partners, and industries to design, develop, and deliver solutions that power digital transformation. With a culture that values innovation, growth, and continuous learning, IBM Software places you at the heart of IBM’s product and technology landscape. Here, you’ll have the tools and opportunities to advance your career while creating software that changes the world.
Your Role And Responsibilities
Confluent is pioneering a fundamentally new category of data infrastructure focused on data in motion. Our cloud-native platform helps organizations connect and process data in real time across applications, databases, and systems.
We’re building a foundational platform for real-time data and are looking for self-motivated engineers who enjoy solving challenging problems, collaborating with others, and growing their technical skills.
About The Role
As a Software Engineer on the Compute Platform team, you will help build and operate the cloud-native compute platform that powers Confluent Cloud workloads.
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Our platform manages workloads across Kubernetes clusters and cloud providers, providing common capabilities for scheduling, lifecycle management, security, and operations. You’ll work with experienced engineers to design, implement, test, and operate reliable systems.
Areas You May Contribute To Include
- Workload orchestration across Kubernetes clusters
- Platform APIs and Kubernetes operators
- Cloud platform integrations
- Multi-tenant workload isolation and security
- Observability, health checks, and operational tooling
- Workload scheduling, disruption management, and rolling updates
What You Will Do
- Design and implement services, APIs, and Kubernetes controllers using Go.
- Contribute to systems that manage workload placement, lifecycle, and state across Kubernetes clusters.
- Work with product managers and engineers to understand requirements and deliver reliable solutions.
- Participate in technical design discussions and help evaluate implementation trade-offs.
- Improve the reliability, scalability, observability, and maintainability of existing systems.
- Write automated tests, documentation, and operational runbooks.
- Participate in code reviews and provide constructive feedback to teammates.
- Help investigate and resolve production issues as part of the team’s operational responsibilities.
- Collaborate with partner teams across Confluent Cloud to support end-to-end platform functionality.
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Preferred Education
Master's Degree
Required Technical And Professional Expertise
- Few years of professional software engineering experience, or equivalent practical experience.
- Experience designing, implementing, and operating production software.
- Proficiency in Go or a similar programming language, with the ability to learn Go.
- Familiarity with Kubernetes concepts such as deployments, services, controllers, or operators.
- Understanding of distributed systems, APIs, networking, or cloud infrastructure.
- Experience with software testing, debugging, monitoring, and incident resolution.
- Ability to break down moderately complex problems and deliver solutions with guidance from teammates.
- Strong written and verbal communication skills.
- A collaborative, thoughtful, and growth-oriented approach to engineering.
Preferred Technical And Professional Experience
- Experience building Kubernetes controllers or operators.
- Experience with gRPC, Protobuf, or API design.
- Experience working with AWS, GCP, Azure, or cloud-provider integrations.
- Familiarity with multi-tenant systems or workload isolation.
- Experience with observability tools and operational best practices.
- Experience with containerized applications and Kubernetes-based platforms.
- Exposure to scheduling, resource management, networking, or infrastructure automation.
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