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# Senior Site Reliability Engineer

- **Company:** Adobe Systems
- **Location:** New York, NY, United States (Remote available)
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** PHP (Programming Language), Artificial Intelligence, Amazon Elastic Compute Cloud, Microsoft Azure, Cloud Computing, Cloud Engineering, Databases, Continuous Integration, Software Debugging, Distributed Systems, Python (Programming Language), Node.Js, Reliability Engineering, Ruby, Azure Machine Learning, Web Services, Autoscaling, Delivery Pipeline, Adobe, AI Platforms, Kubernetes, Information Technology, Patch Management, Machine Learning Operations
- **Published:** August 7, 2026
- **Apply:** https://us.experteer.com/career/view-jobs/senior-site-reliability-engineer-new-york-ny-usa-58832290

## About the Role

Experteer Overview In this Senior SRE role you will design, build, and operate large-scale, distributed infrastructure that enables AI-powered products. You'll own patching, image lifecycle, and security guardrails while collaborating with software, ML, and platform teams to bake reliability in from the start. You'll work across cloud-native environments, ML inference pipelines, and on-call rotations to keep systems resilient. This is a hands-on opportunity to shape scalable cloud and AI platforms at Adobe. Compensation / Benefits * Design, build, and operate large-scale, distributed systems and the tooling behind them (IaC, CI/CD, automation) * Own patch, vulnerability, and golden-image lifecycle management at fleet scale * Contribute to multi-quarter initiatives (compute rationalization, cloud re-platforming, ML platform migration) * Build and operate ML inference infrastructure (model serving, GPU workloads, language model gateway/routing) * Help set infrastructure standards and aa
behind guardrails for agentic AI; develop agent tooling for operations * Partner with software, ML, and platform teams to bake reliability in from the start * Share on-call duties and address issues across web services, databases, and pipelines Tasks * BSc in Computer Science or equivalent * Python (plus familiarity with PHP, Node.js, or Ruby) * Experience deploying/operating ML inference pipelines in production (SageMaker, OpenAI, Bedrock, or equivalent) * Experience with cloud-native compute at scale (AWS EC2 Auto Scaling Groups, Kubernetes; Azure/GCP a plus) * Experience with vulnerability/patch management and AMI/golden-image automation * Strong debugging skills on distributed systems * Willingness to participate in on-call rotation Key requirements * remote work * growth opportunities in AI * collaborative culture * security and guardrails focus * infrastructure modernization * competitive pay range

## Description

Experteer Overview In this Senior SRE role you will design, build, and operate large-scale, distributed infrastructure that enables AI-powered products. You'll own patching, image lifecycle, and security guardrails while collaborating with software, ML, and platform teams to bake reliability in from the start. You'll work across cloud-native environments, ML inference pipelines, and on-call rotations to keep systems resilient. This is a hands-on opportunity to shape scalable cloud and AI platforms at Adobe. Compensation / Benefits * Design, build, and operate large-scale, distributed systems and the tooling behind them (IaC, CI/CD, automation) * Own patch, vulnerability, and golden-image lifecycle management at fleet scale * Contribute to multi-quarter initiatives (compute rationalization, cloud re-platforming, ML platform migration) * Build and operate ML inference infrastructure (model serving, GPU workloads, language model gateway/routing) * Help set infrastructure standards and security guardrails for agentic AI; develop agent tooling for operations * Partner with software, ML, and platform teams to bake reliability in from the start * Share on-call duties and address issues across web services, databases, and pipelines Tasks * BSc in Computer Science or equivalent * Python (plus familiarity with PHP, Node.js, or Ruby) * Experience deploying/operating ML inference pipelines in production (SageMaker, OpenAI, Bedrock, or equivalent) * Experience with cloud-native compute at scale (AWS EC2 Auto Scaling Groups, Kubernetes; Azure/GCP a plus) * Experience with vulnerability/patch management and AMI/golden-image automation * Strong debugging skills on distributed systems * Willingness to participate in on-call rotation Key requirements * remote work * growth opportunities in AI * collaborative culture * security and guardrails focus * infrastructure modernization * competitive pay range


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