Cognizant is seeking an AI Site Reliability Engineer to build and operate the reliable, scalable, and secure infrastructure behind our AI and machine-learning 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 our AI systems meet high standards for availability, latency, performance, cost, and operational safety.
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.
Required 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.
Preferred Qualifications
• Experience operating machine-learning or generative-AI workloads in production.
• Familiarity with GPUs, CUDA, model-serving systems, vector databases, or high-performance computing.
• Experience with tools such as Prometheus, Grafana, OpenTelemetry, Argo CD, Helm, or service meshes.
• Knowledge of MLOps practices, model lifecycle management, and ML/data pipelines.
• Experience with reliability testing, chaos engineering, load testing, or capacity modeling.
• Understanding of AI security, data privacy, model-safety controls, and access management.
Success in This Role
Within the first year, you will help reduce critical incidents, improve detection and recovery times, increase platform availability, improve infrastructure utilization, and create repeatable operational standards for deploying and running AI systems at scale.
The salary range for this role is between $142,000 and $167,500 depending on skills and qualifications of the candidate. Applications will be accepted till 10/31/2026
コグニザントについて
コグニザント（NASDAQ: CTSH）は、AI Builderおよびテクノロジーサービスプロバイダーとして、お客様にフルスタックのAIソリューションを構築することで、AI投資と企業価値を結ぶ架け橋となっています。業界、ビジネスプロセス、エンジニアリングに関する当社の深い専門知識を活かし、組織固有のビジネス環境をテクノロジー・システムに組み込みます。これにより、人間の可能性を最大限に引き出し、確かな成果を実現するとともに、急速に変化する世界においてグローバル企業が常に一歩先を行くための支援を行っています。 詳細については、cognizant.ai をご覧ください。
雇用に関する追加情報
本募集に記載されている報酬情報は、掲載日時点で正確なものです。Cognizantは、適用される法令に従い、いつでも本情報を変更する権利を留保します。
応募者は、対面またはビデオ会議による面接への参加を求められる場合があります。また、各面接の際に、現在有効な州政府または政府発行の身分証明書の提示を求められる場合があります。
Cognizantは機会均等雇用主です。応募および選考において、人種、肌の色、性別、宗教、信条、性的指向、性自認、国籍、障がい、遺伝情報、妊娠、退役軍人の地位、その他連邦法・州法・地方自治体の法律により保護されるいかなる特性に基づく差別も行いません。
