Senior DevOps Engineer (AI Ops)

Adobe•San Jose, CA

About The Position

We are seeking a hands-on Senior DevOps Engineer specializing in AI Ops to own infrastructure provisioning, CI/CD automation, telemetry pipelines, and production deployment for AI-powered services, agents, and orchestration systems. This role is responsible for building and operating the infrastructure that enables reliable, observable, and scalable AI systems in production. The engineer will help operationalize AI platforms by implementing intelligent monitoring, automated incident response, model lifecycle governance, and data-driven operational insights. The role is SRE-heavy and infrastructure-first, with responsibility for ensuring that systems and services using advanced technology running in production are reliable, resilient, scalable, secured, and cost-effective.

Requirements

Hands-on Senior DevOps Engineer specializing in AI Ops
Own infrastructure provisioning, CI/CD automation, telemetry pipelines, and production deployment for AI-powered services, agents, and orchestration systems.
Build and operate the infrastructure that enables reliable, observable, and scalable AI systems in production.
Help operationalize AI platforms by implementing intelligent monitoring, automated incident response, model lifecycle governance, and data-driven operational insights.
SRE-heavy and infrastructure-first experience
Experience with Infrastructure as Code (Terraform, etc.)
Experience provisioning and maintaining Kubernetes clusters and supporting services
Experience automating environment setup across dev, stage, and production
Experience building and maintaining CI/CD pipelines for AI Services, Agent Frameworks, Orchestrators, and Model Artifacts
Experience implementing automated testing and reliability validation gates
Experience building safe rollback mechanisms for services and models
Experience integrating reliability and health checks into deployment workflows
Experience packaging, versioning, and deploying models and agent services in containerized environments
Experience managing artifact promotion across environments.
Experience monitoring model and agent performance (latency, throughput, accuracy, cost)
Experience enabling safe rollout, rollback, and refresh workflows.
Experience designing and operating scalable pipelines for collecting and processing logs, metrics, traces, and operational events.
Experience enabling structured telemetry for AI services and orchestration systems to support real-time monitoring and operational insights.
Experience with AIOps Platform Integration
Experience ensuring production reliability and SRE excellence
Eager to innovate with AI

Nice To Haves

Experience with AI Ops

Responsibilities

Design and manage cloud infrastructure using Infrastructure as Code (Terraform, etc.)
Provision and maintain Kubernetes clusters and supporting services
Automate environment setup across dev, stage, and production
Build and maintain CI/CD pipelines for AI Services, Agent Frameworks, Orchestrators, and Model Artifacts
Implement automated testing and reliability validation gates
Build safe rollback mechanisms for services and models
Integrate reliability and health checks into deployment workflows
Package, version, and deploy models and agent services in containerized environments while managing artifact promotion across environments.
Monitor model and agent performance (latency, throughput, accuracy, cost) and enable safe rollout, rollback, and refresh workflows.
Design and operate scalable pipelines for collecting and processing logs, metrics, traces, and operational events.
Enable structured telemetry for AI services and orchestration systems to support real-time monitoring and operational insights.
Integrate AIOps Platform
Ensure systems and services using advanced technology running in production are reliable, resilient, scalable, secured, and cost-effective.