About the Job

Do you want to help shape the future of AI by building robust infrastructure and tools for developing trustworthy large language models and agentic workflows? We're seeking a software engineer who combines strong systems engineering skills with a passion for AI safety to develop frameworks that ensure AI systems behave reliably and align with human values. 

The OpenShift AI team is looking for a Senior Software Engineer with Kubernetes and MLOps or LLMOps experience to join our rapidly growing engineering team. Our team’s focus is to make machine learning model deployment and monitoring seamless, scalable, and trustworthy across the hybrid cloud and the edge. This is a very exciting opportunity to build and impact the next generation of hybrid cloud MLOps platforms.

 

In this role, you'll be contributing as a technical infrastructure expert for responsible AI features of the open source Open Data Hub project by actively participating in KServe, TrustyAI, Kubeflow, and several other open source communities. You will work as part of an evolving development team to rapidly design, secure, build, test and release model serving, trustworthy AI, and model registry capabilities. The role is primarily an individual contributor who will be a key notable contributor to trustworthy AI and MLOps/LLMOps upstream communities and collaborate  closely with the internal cross-functional development teams. 

What you will do

Lead the architecture and implementation of MLOps/LLMOps systems within OpenShift AI, establishing best practices for scalability, reliability, and maintainability while actively contributing to relevant open source communities

Design and develop robust, production-grade features focused on AI trustworthiness, including model monitoring, bias detection, and explainability frameworks that integrate seamlessly with OpenShift AI

Drive technical decision-making around system architecture, technology selection, and implementation strategies for key MLOps components, with a focus on open source technologies like KServe and TrustyAI

Define and implement technical standards for model deployment, monitoring, and validation pipelines, while mentoring team members on MLOps best practices and engineering excellence

Collaborate with product management to translate customer requirements into technical specifications, architect solutions that address scalability and performance challenges, and provide technical leadership in customer-facing discussions

Lead code reviews, architectural reviews, and technical documentation efforts to ensure high code quality and maintainable systems across distributed engineering teams

Identify and resolve complex technical challenges in production environments, particularly around model serving, scaling, and reliability in enterprise Kubernetes deployments

Partner with cross-functional teams to establish technical roadmaps, evaluate build-vs-buy decisions, and ensure alignment between engineering capabilities and product vision

Provide technical mentorship to team members, including code review feedback, architecture guidance, and career development support while fostering a culture of engineering excellence 

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What you will bring

5+ years of software engineering experience, with at least 4 years focusing on ML/AI systems in production environments

Strong expertise in Python, with demonstrated experience building and deploying production ML systems

Deep understanding of Kubernetes and container orchestration, particularly in ML workload contexts

Extensive experience with MLOps tools and frameworks (e.g., KServe, Kubeflow, MLflow, or similar)

Track record of technical leadership in open source projects, including significant contributions and community engagement

Proven experience architecting and implementing large-scale distributed systems

Strong background in software engineering best practices, including CI/CD, testing, and monitoring

Experience mentoring engineers and driving technical decisions in a team environment

 

The following will be considered a plus: 

Experience with Red Hat OpenShift or similar enterprise Kubernetes platforms

Contributions to ML/AI open source projects, particularly in the MLOps space

Background in implementing ML model monitoring, explainability, or bias detection systems

Experience with LLM operations and deployment at scale

Public speaking experience at technical conferences

Advanced degree in Computer Science, Machine Learning, or related field

Experience working with distributed engineering teams across multiple time zones

Familiarity with AI governance and responsible AI practices

#LI-MD2

The salary range for this position is $111,260.00 - $183,580.00. Actual offer will be based on your qualifications.

Pay Transparency

Red Hat determines compensation based on several factors including but not limited to job location, experience, applicable skills and training, external market value, and internal pay equity. Annual salary is one component of Red Hat’s compensation package. This position may also be eligible for bonus, commission, and/or equity. For positions with Remote-US locations, the actual salary range for the position may differ based on location but will be commensurate with job duties and relevant work experience. 

About Red Hat

Red Hat is the world’s leading provider of enterprise open source software solutions, using a community-powered approach to deliver high-performing Linux, cloud, container, and Kubernetes technologies. Spread across 40+ countries, our associates work flexibly across work environments, from in-office, to office-flex, to fully remote, depending on the requirements of their role. Red Hatters are encouraged to bring their best ideas, no matter their title or tenure. We're a leader in open source because of our open and inclusive environment. We hire creative, passionate people ready to contribute their ideas, help solve complex problems, and make an impact.

Benefits
●    Comprehensive medical, dental, and vision coverage
●    Flexible Spending Account - healthcare and dependent care
●    Health Savings Account - high deductible medical plan
●    Retirement 401(k) with employer match
●    Paid time off and holidays
●    Paid parental leave plans for all new parents
●    Leave benefits including disability, paid family medical leave, and paid military leave
●    Additional benefits including employee stock purchase plan, family planning reimbursement, tuition reimbursement, transportation expense account, employee assistance program, and more! 

Note: These benefits are only applicable to full time, permanent associates at Red Hat located in the United States. 

Diversity, Equity & Inclusion at Red Hat
Red Hat’s culture is built on the open source principles of transparency, collaboration, and inclusion, where the best ideas can come from anywhere and anyone. When this is realized, it empowers people from diverse backgrounds, perspectives, and experiences to come together to share ideas, challenge the status quo, and drive innovation. Our aspiration is that everyone experiences this culture with equal opportunity and access, and that all voices are not only heard but also celebrated. We hope you will join our celebration, and we welcome and encourage applicants from all the beautiful dimensions of diversity that compose our global village.

Equal Opportunity Policy (EEO)
Red Hat is proud to be an equal opportunity workplace and an affirmative action employer. We review applications for employment without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, ancestry, citizenship, age, veteran status, genetic information, physical or mental disability, medical condition, marital status, or any other basis prohibited by law.

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