{"id":2148805,"url":"https://alion.io/job/cognizant-senior-site-reliability-engineer","title":"Senior Site Reliability Engineer","company":{"id":85,"name":"Cognizant","domain":"cognizant.com","url":"https://alion.io/company/cognizant","size_band":"5000+","is_staffing_agency":false,"employer_type":"services","is_intermediary":false,"listed_via":null,"ats_vendor":"Cognizant Careers","truth_index":{"grade":"A","score":87,"open_postings":114,"ghost_share":0,"stale_share":0.728,"repost_share":0.018,"time_to_fill_p50_days":20,"computed_at":"2026-10-21T05:46:15Z"}},"role":"DevOps","role_family":"DevOps","seniority":"senior","employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"explicit","locations":["Arizona City, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":84000,"max_usd":160000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":1716},"experience_years_min":null,"visa_sponsorship":true,"relocation_package":false,"has_equity":true,"technologies":[{"name":"AIOps","optional":false},{"name":"Anomaly Detection","optional":false},{"name":"Ansible","optional":false},{"name":"CI/CD","optional":false},{"name":"Configuration Management","optional":false},{"name":"GCP","optional":false},{"name":"Git","optional":false},{"name":"GitHub Actions","optional":false},{"name":"Google GKE","optional":false},{"name":"Grafana","optional":false},{"name":"Helm","optional":false},{"name":"Incident Management","optional":false},{"name":"Java","optional":false},{"name":"Kubeflow","optional":false},{"name":"Kubernetes","optional":false},{"name":"Linux","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"Node JS","optional":false},{"name":"Prometheus","optional":false},{"name":"Python","optional":false},{"name":"Spring Boot","optional":false},{"name":"Terraform","optional":false},{"name":"Vertex AI","optional":false},{"name":"JavaScript","optional":true}],"status":"live","first_seen_at":"2026-09-24T14:44:03Z","employer_posted_date":"2026-10-09","last_verified_at":"2026-10-21T12:41:05Z","board_verified":true,"closed_at":null,"days_open":27,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":27},"description":"About the Role\nAs a Senior Site Reliability Engineer you will make an impact by leading the operational excellence, reliability, and continuous improvement of AI-powered digital platforms supporting healthcare payer operations. You will oversee hybrid-cloud services leveraging Large Language Models (LLMs), MLOps practices, cloud-native technologies, and modern engineering frameworks to deliver secure, scalable, and compliant solutions that enhance member and provider experiences.\nYou will be a valued member of the Technology & Engineering team, collaborating closely with business stakeholders, product teams, platform engineers, AI specialists, and operations teams to ensure service stability, innovation, and regulatory compliance.\nIn This Role, You Will:\nOwn end-to-end service accountability for payer-focused AI, LLM, and ML-enabled platforms, ensuring high availability, performance, and compliance across hybrid environments.\nLead operational governance and continuous improvement initiatives aligned with enterprise service management best practices.\nOversee MLOps processes supporting LLM-powered applications, including model deployment, monitoring, retraining, validation, and rollback strategies.\nCoordinate the deployment and lifecycle management of containerized services utilizing Kubernetes to deliver scalable, resilient, and highly available solutions.\nImplement and govern Infrastructure as Code (IaC) practices using Terraform to provision and manage cloud and on-premises resources consistently and securely.\nStandardize configuration management through Ansible automation to improve operational efficiency and reduce service disruptions.\nSupport the development, deployment, and operational management of Node.js-based services and APIs that integrate AI and machine learning capabilities.\nEstablish best practices for Git-based version control, release management, code reviews, and repository governance across application and infrastructure teams.\nDrive operational excellence across Linux environments, including security hardening, patch management, performance optimization, and system monitoring.\nGuide Python-based development supporting data pipelines, AI orchestration, automation frameworks, and analytics workloads.\nCollaborate with business stakeholders, product owners, and healthcare domain experts to translate complex payer requirements into reliable technology services.\nLead incident management, root cause analysis, problem management, and service restoration activities to minimize business impact.\nMonitor platform health through metrics, logs, traces, and observability tools while continuously improving service reliability and resilience.\nFoster a culture of knowledge sharing, operational excellence, automation, and continuous improvement across distributed teams.\nWork Model\nWe believe hybrid work is the way forward as we strive to provide flexibility wherever possible. Based on this role's business requirements, this is a hybrid position requiring attendance at a client or Cognizant office based on project needs.\nThe working arrangements for this role are accurate as of the date of posting and may change according to client and business requirements.\nWhat You Need to Have to Be Considered\nStrong experience with Kubernetes and GCP (GKE) \nStrong experience in IaC (Terraform), Helm, and GitHub Actions \nProficiency in Python, Ansible, Node.js \nStrong experience with Prometheus and Grafana observability stack \nSolid understanding of Linux systems and networking fundamentals \nExperience in incident management, on-call support, and production triage \nHands-on experience with automation and CI/CD pipelines\nStrong understanding of AI/ML concepts and AIOps practices (model lifecycle, monitoring, or AI-driven alerting)\nThese Will Help You Stand Out\nGoogle Cloud Architect Certification \nCertified Kubernetes Administrator (CKA) \nExperience in Java/J2EE, Spring Boot \nExperience supporting or operating ML/AI platforms or pipelines (MLOps)\nExposure to AIOps tools, anomaly detection, or predictive analytics systems\nExperience with large-scale distributed systems and microservices architecture\nExperience with GPU-based workloads or ML infrastructure on GCP\nKnowledge of Kubeflow, Vertex AI, or ML pipelines\nExperience integrating AI-driven automation into monitoring and incident response\nBenefits: \nCognizant offers the following benefits for this position, subject to applicable eligibility requirements:\nMedical/Dental/Vision/Life Insurance. \nPaid holidays plus Paid Time Off. \n401(k) plan and contributions. \nLong-term/Short-term Disability. \nPaid Parental Leave. \nEmployee Stock Purchase Plan.**Please note: A few of our roles may require in-person interviews at Cognizant offices or client locations, depending on project or client needs.**\n**Candidate must be legally authorized to work in the United States without the need for employer sponsorship, now or at any time in the future\n\nWhy Cognizant?\nAt Cognizant, we're engineering modern businesses through innovation, technology, and human-centered solutions. You'll work with talented professionals, cutting-edge technologies, and industry-leading clients while helping shape the future of AI-driven healthcare solutions.\nWe're excited to meet people who share our mission and can make an impact in a variety of ways. Don't hesitate to apply, even if you don't meet every requirement. 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