Senior Software Engineer, AI Model Serving

Job Summary

Are you ready to join a game-changing open-source AI platform that harnesses the power of hybrid cloud to drive innovation?

The Red Hat OpenShift AI (RHOAI) team is looking for a Senior Software Engineer with Kubernetes and MLOps (Machine Learning) experience to join our rapidly growing engineering team. Our focus is to create a platform, partner ecosystem, and community by which enterprise customers can solve problems to accelerate business success using AI. This is a very exciting opportunity to build and impact the next generation of hybrid cloud MLOps platforms, contribute to the development of the RHOAI product, participate in open-source communities, and be at the forefront of the exciting evolution of AI. You’ll join an ecosystem that fosters continuous learning, career growth, and professional development. 

As a core developer for the Model Server and Metrics team in Red Hat Openshift AI, you will have the opportunity to actively participate in one of our main components in AI space as well as the affiliated open-source communities, such as KServe, Kubeflow, and vLLM. You will work as part of an evolving development team to rapidly design, secure, build, test, and release new capabilities. The role is primarily an individual contributor who collaborates closely with other developers and cross-functional teams. You should have a passion for working in open-source communities and for developing solutions that integrate Red Hat, open-source, and partner technologies into a cohesive platform.

At Red Hat, our commitment to open source innovation extends beyond our products - it’s embedded in how we work and grow. Red Hatters embrace change – especially in our fast-moving technological landscape – and have a strong growth mindset. That's why we encourage our teams to proactively, thoughtfully, and ethically use AI to simplify their workflows, cut complexity, and boost efficiency. This empowers our associates to focus on higher-impact work, creating smart, more innovative solutions that solve our customers' most pressing challenges.

What you will do:

• Contribute to the architecture, design, development, and testing of new features and solutions for RHOAI

• Innovate in the MLOps domain by participating in upstream communities, such as KubeFlow and KServe

• Ensure non-functional requirements including security, resiliency, and maintainability are met

• Write unit and integration tests and work with quality engineers to ensure product quality

• Use CI/CD best practices to deliver solutions as productization efforts into RHOAI

• Contribute to a culture of continuous improvement by sharing recommendations and technical knowledge with team members

• Collaborate with product management, other engineering and cross-functional teams to analyze and clarify business requirements

• Communicate effectively to stakeholders and team members to ensure proper visibility of development efforts

• Give thoughtful and prompt code reviews

• Represent RHOAI in external engagements including industry events, customer meetings, and open-source communities

• Mentor and guide other engineers

• Give thoughtful and prompt code reviews

• Proactively utilize AI-assisted development tools (e.g., GitHub Copilot, Cursor, Claude Code) for code generation, auto-completion, and intelligent suggestions to accelerate development cycles and enhance code quality.

• Explore and experiment with emerging AI technologies relevant to software development, proactively identifying opportunities to incorporate new AI capabilities into existing workflows and tooling

What you will bring:

• Minimum of 5 years of experience

• Passion for writing and maintaining reliable code

• Experience with monitoring and alerting tools such as Prometheus and Grafana

• Excellent written and verbal communication skills; fluent English language skills

• Strong experience developing applications in Python, GoLang is a plus

• Strong experience in Kubernetes or OpenShift 

• Experience  with source code management tools such as Git

• Strong system understanding and troubleshooting capabilities

• Autonomous work ethic, thriving in a dynamic, fast-paced environment

• Familiarity with data science workflows and machine learning pipelines

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