Site Reliability Engineering Manager, AI Platform

Site Reliability Engineering Manager, AI Platform

Our Company

Changing the world through digital experiences is what Adobe’s all about. We give everyone—from emerging artists to global brands—everything they need to design and deliver exceptional digital experiences! We’re passionate about empowering people to create beautiful and powerful images, videos, and apps, and transform how companies interact with customers across every screen.

We’re on a mission to hire the very best and are committed to creating exceptional employee experiences where everyone is respected and has access to equal opportunity. We realize that new ideas can come from everywhere in the organization, and we know the next big idea could be yours!

The Opportunity
We're looking for an outstanding, hands-on leader to drive Reliability for Adobe’s AI Inference Platform, Adobe Firefly. You will develop a team of Site Reliability Engineers closely working with the Engineering teams on building, scaling, and securing the AI Platform. This enables the Firefly product teams to easily manage and deploy Machine Learning capabilities used by Adobe client applications. The Applied Research groups from Adobe Research and other App Teams in Adobe will deploy thousands of models onto this platform in a variety of lifecycle stages (early research, development, productization, optimization, etc). This platform will offer an ML model serving at scale, with high-cost efficiency, and on a wide variety of hardware platforms across multiple clouds.
What You'll Do

• Guide the technical vision and roadmap for AI Platform Inference infrastructure.
• Grow and lead a team of dedicated SRE engineers.
• Engage with Firefly Engineering and Firefly App Integrations team to understand their needs and goals to drive the platform's reliability.
• Identify and implement methodologies and solutions to increase reliability, scalability, security, and efficiency.
• Ensure the highest uptime and Quality of Service (QoS) for Adobe’s customers through operational excellence.
• Define service level objectives (SLOs) and indicators (SLIs) to represent and measure service quality.
• Support and maintain globally distributed, multi-cloud (public and/or private) environments.
• Automate common, repeatable tasks at a large scale to streamline operational procedures.
• Identify areas to improve service resiliency through techniques such as chaos engineering, performance/load testing, etc.
• Coordinate with other Adobe platform teams and service providers (primarily AWS) to innovate on Generative AI as a Service.
• Ensure inference services improve GPU utilization, scale models independently, and optimize COGs.

What You’ll Need to Succeed

• A BS or MS degree in Computer Science, Electrical Engineering, a related field, or equivalent industry experience.
• You have 3+ years of experience as an Engineering Manager.
• You excel in undefined environments and get excited about finding pragmatic solutions to complex technical or organizational challenges.
• You've worked with high-scale distributed systems used by tens or hundreds of millions of users.
• You are passionate about coaching and developing engineers but love to dig into technical problems when the opportunity arises.
• You keep up with the industry trends and grow your knowledge and skills to solve technical problems.
• Experience in building and scaling distributed systems, as well as experience with containerization and orchestration technologies like Kubernetes.
• Strong communication and collaboration skills - building strong relationships with internal customers and external partners.
• Dedication to teamwork, self-organization, and continuous improvement.
• A track record of leading high-performance teams to deliver results in a fast-paced and dynamic environment of AI infrastructure.
• Production level expertise with containerization orchestration engines (e.g. Kubernetes) and demonstrated understanding of modern, continuous development techniques and pipelines (IaC, CI/CD, ArgoCD, Git).
• Fundamental programming skills, ideally practical experience in one (and preferably more) of the following languages: Python, Go or Java.
• An understanding of AI/ML, including ML frameworks, public cloud, and commercial AI/ML solutions - familiarity with Pytorch, SageMaker, HuggingFace, NVIDIA TensorRT or OpenAI Triton a plus.

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