Deployment Engineer

Position: Senior Deployment Engineer – Cloud, Data & AI PlatformsLocation: Montvale, NJ & Iselin, NJ (Onsite three days a week)Employment: ContractExperience: 10+ yearsJob Description:Seeking a Senior Deployment Engineer to lead the deployment, automation, and operational enablement of enterprise‑scale cloud, data, and AI platforms. This role is critical to ensuring production‑ready, secure, and scalable deployments across analytics, AI, and digital platforms. The engineer will work closely with KPMG’s cloud platform, data engineering, AI, DevOps, and security teams. The role requires deep hands‑on expertise combined with the ability to own deployment strategy, improve platform standards.Key ResponsibilitiesEnterprise Platform Deployment LeadershipLead end‑to‑end deployment of complex cloud, data, and AI platforms across mostly Azure but also AWSOwn deployment architecture, standards, and operational readiness for non‑prod and production environmentsServe as the senior escalation point for deployment‑related failures, instability, or performance issuesDevOps & CI/CD ExcellenceDesign, build, and optimize enterprise‑grade CI/CD pipelines for application, data, and AI workloadsEstablish and enforce deployment best practices including versioning, rollback strategies, and environment parityDrive automation to minimize manual deployment effort and reduce operational riskKubernetes & Container PlatformsLead deployment and operations of containerized platforms on AKS (Azure Kubernetes Service)Manage cluster configuration, scaling, ingress/egress, secrets, and workload isolationSupport container security, resilience, and high availability standardsData & Analytics Platform EnablementOwn deployment and operationalization of Databricks and Microsoft Fabric environmentsSupport enterprise data workloads including Lakehouse architectures, analytics pipelines, and platform integrationsPartner with data engineering teams to ensure deployments are optimized for scale, cost, and performanceAI Platform DeploymentLead deployment of AI solutions using Azure OpenAI ServiceSupport environment configuration, endpoint management, security controls, and production hardeningOperationalize AI workloads responsibly and securelyInfrastructure as Code & Cloud EngineeringBuild and maintain Infrastructure as Code (IaC) using Terraform, ARM/Bicep, or CloudFormationEnsure cloud resources follow enterprise security, networking, and governance standardsOptimize cloud environments for cost efficiency, performance, and reliabilitySecurity, Monitoring & ComplianceImplement and enforce cloud security best practices (IAM, secrets, encryption, network isolation)Own monitoring, logging, and alerting strategy across deployed platformsSupport audits, compliance reviews, and production readiness validations in regulated environments Core Expertise (Senior‑Level)DevOps & Deployment Engineering in large‑scale enterprise environmentsAzure Cloud (strong experience across computer, networking, security, and governance)AKS (Azure Kubernetes Service) – production deployment and operationsDatabricks – enterprise deployment and platform enablementMicrosoft Fabric – environment setup and operational supportAI Platforms – experience deploying solutions using Azure OpenAI ServiceAWS Cloud – hands‑on deployment and operational understandingTooling & TechnologiesCI/CD platforms (Azure DevOps, GitHub Actions, Jenkins, or equivalent)Infrastructure as Code: Terraform, ARM templates, Bicep, CloudFormationContainers & orchestration: Docker, KubernetesMonitoring & observability: Azure Monitor, Log Analytics, CloudWatch, Prometheus Qualifications & Experience8+ years of experience in Cloud, DevOps, or Deployment Engineering rolesProven experience leading deployments for data, analytics, and AI platformsStrong background supporting production enterprise systemsExperience in regulated or audit‑driven environments is highly preferredAbility to operate independently and lead complex deployment initiatives end‑to‑end