About the Job: The Data Development Insights Strategy (DDIS) team at Red Hat is seeking an AI Engineering Manager to lead a talented team of AI Engineers focused on the design, deployment, and optimization of AI model lifecycle frameworks within our OpenShift AI and RHEL AI infrastructures. As an AI Engineering Manager, you will be responsible for driving the technical vision and execution of AI model lifecycle management at scale, overseeing the development and deployment of cutting-edge AI technologies while ensuring the scalability, performance, and security of mission-critical AI models. In this leadership role, you will work closely with cross-functional teams, including Products Global Engineering (PGE) and IT AI Infra teams, to drive the deployment, maintenance and optimization of AI models and infrastructure, ensuring alignment with business objectives and strategic goals. You will be tasked with managing and mentoring a high-performing team of AI Engineers, driving innovation, setting technical priorities, and fostering a collaborative and growth-oriented team culture. This is an ideal role for someone with a strong background in AI/ML, MLOps, and leadership, looking to have a significant impact on Red Hats AI strategy and innovations. What you will do Lead and manage a team of AI Engineers, providing mentorship, guidance, and fostering a culture of continuous learning, collaboration, and technical excellence. Define and execute the technical strategy for AI model lifecycle management, ensuring the scalability, security, and optimization of AI models within Red Hats OpenShift and RHEL AI infrastructures. Oversee the development, deployment, and maintenance of AI models, working with engineering teams to ensure seamless integration, minimal downtime, and high availability in production environments. Drive the implementation of automation, CI/CD pipelines, and Infrastructure as Code (IaC) practices to streamline AI model deployment, updates, and monitoring. Collaborate with cross-functional teams (PGE, IT AI Infra, etc.) to ensure that AI models and infrastructure meet evolving business needs, data changes, and emerging technology trends. Manage and prioritize the resolution of feature requests (RFEs), ensuring timely, transparent communication and effective problem resolution. Guide the optimization of large-scale models, including foundational models like Mistral and LLama, and ensure optimal computational resource management (e.g., GPU optimization, cost management strategies). Lead efforts to monitor and enhance AI model performance, using advanced tools (OpenLLMetry, Splunk, Catchpoint) to identify and resolve performance bottlenecks. Define and track key performance metrics for AI models, ensuring that model updates and releases meet business expectations and deadlines (e.g., quarterly releases, RFEs resolved within 30 days). Foster collaboration between teams to ensure that model updates and optimizations align with both business objectives and technological advancements. Promote innovation by staying up-to-date with emerging AI technologies, tools, and industry trends, and integrating these advancements into Red Hats AI infrastructure. Take ownership of the teams growth and professional development, ensuring engineers are continuously challenged and supported in their career progression. What you will bring A bachelors or masters degree in Computer Science, Data Science, Machine Learning, or a related technical field, although hands-on experience and demonstrated leadership in AI engineering and MLOps can be considered in lieu of formal academic credentials. 10+ years of experience in AI engineering, MLOps, or related fields, and at least 3 years of leadership experience, you will have a strong background in managing high-performing engineering teams and mentoring Principal and Senior Engineers. Foster a culture of technical excellence, continuous improvement, and innovation within the team. Expertise in deploying, maintaining, and optimizing AI models at scale across cloud environments such as AWS, GCP, or Azure, and containerized platforms like OpenShift or Kubernetes. Experience with AI/ML frameworks, performance monitoring, and resource optimization (e.g., CUDA, MIG, vLLM, TGI) will ensure that AI models are efficient, scalable, and high-performing. Hands-on experience with Infrastructure as Code (IaC) practices, CI/CD tools (Git, Jenkins, Terraform), and automating AI model deployment and monitoring pipelines. Strong problem-solving skills for optimizing and troubleshooting large-scale AI systems and distributed architectures. Excellent communication skills, with the ability to interact effectively with both technical and non-technical stakeholders. Desired skills: 10+ years of experience in AI, MLOps, or related fields, including 3+ years of leadership experience. Experience in managing large-scale AI infrastructure, particularly in high-performance computing environments. Deep expertise in AI model lifecycle management, from development to deployment, monitoring, and performance optimization. A strong background in cross-functional collaboration, driving alignment between business objectives, engineering teams, and technical requirements. Proven ability to innovate, set technical direction, and deliver AI infrastructure improvements at scale. As an AI Engineering Manager at Red Hat, you will have the opportunity to shape the future of AI model lifecycle management at scale, influence strategic initiatives, and drive innovation across a high-performing engineering team. If youre a dynamic leader with a passion for AI and machine learning, and want to make a significant impact on Red Hats AI infrastructure, we encourage you to apply. About Red Hat is the worlds leading provider of enterprise 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. Diversity, Equity Inclusion at Red Hat Red Hats 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. Red Hat does not seek or accept unsolicited resumes or CVs from recruitment agencies. We are not responsible for, and will not pay, any fees, commissions, or any other payment related to unsolicited resumes or CVs except as required in a written contract between Red Hat and the recruitment agency or party requesting payment of a fee. Red Hat supports individuals with disabilities and provides reasonable accommodations to job applicants. If you need assistance completing our online job application, email . 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