AI Platform Reliability Engineer

Cognizant; San Jose (CA); On-site; USD 142,000 - 168,000; Full time

Job summary

Cognizant is seeking an AI Site Reliability Engineer to build and operate reliable, scalable infrastructure behind AI and ML platforms. You will work across cloud infrastructure, Kubernetes, GPU compute, model-serving systems, observability, automation, and incident response.

You will partner with software, data science, security, and platform teams to ensure AI systems meet high standards for availability, latency, and cost.

Qualifications

• 4+ years of experience in SRE, infrastructure engineering, DevOps, platform engineering, or production engineering.
• Strong Linux, networking, cloud, and distributed-systems experience.
• Hands-on experience with Kubernetes and infrastructure-as-code tools such as Terraform.
• Experience with at least one major cloud platform: AWS, Azure, or Google Cloud.
• Proficiency in Python, Go, or another programming language used for automation and production systems.
• Experience with observability platforms, metrics, logs, traces, and incident-management practices.
• Experience operating production services with defined availability and performance targets.
• Strong troubleshooting, communication, documentation, and systems-thinking skills.

Responsibilities

• Design, operate, and improve highly available infrastructure for AI training, inference, and data-processing workloads.
• Define and manage service-level objectives, reliability metrics, error budgets, and capacity plans.
• Build monitoring, logging, tracing, alerting, and AI-specific observability for model-serving platforms.
• Lead incident response, root-cause analysis, post-incident reviews, and reliability improvements.
• Automate deployment, scaling, rollback, disaster recovery, and routine operational tasks.
• Operate Kubernetes-based services, cloud platforms, GPU clusters, networking, storage, and CI/CD systems.
• Improve model-serving performance, including latency, throughput, GPU utilization, availability, and cost efficiency.
• Develop safe automation and self-healing workflows for common production issues.
• Establish operational standards for model versioning, rollouts, canary releases, feature flags, and rollback procedures.
• Collaborate with engineering and ML teams to make AI systems production-ready.
• Maintain clear runbooks, architecture documentation, and operational procedures.
• Participate in an on-call rotation and help build a sustainable, low-noise operational culture.

Skills

Linux

Networking

Cloud platforms

Kubernetes

Terraform

Python/Go

Observability

Incident management

On-call

Tools

Terraform

Prometheus

Grafana

OpenTelemetry

Argo CD

Helm

Service meshes

Job description

Cognizant is seeking an AI Site Reliability Engineer to build and operate reliable, scalable infrastructure behind AI and ML platforms. You will work across cloud infrastructure, Kubernetes, GPU compute, model-serving systems, observability, automation, and incident response.

You will partner with software, data science, security, and platform teams to ensure AI systems meet high standards for availability, latency, and cost.