Senior Deployment Engineer (Cloud, Data & AI Platforms)

Job Title: Senior Deployment Engineer (Cloud, Data & AI Platforms)Job Location: Montvale, NJ & Iselin, NJ (Onsite three days a week)Job Type – Contract Visa: EAD,, GC-EAD, H4EAD, L2-EAD, O1, OPT-EAD,TN Visa, US CitizenJob Description Role Summary We are 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 KPMG’s 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 Responsibilities Enterprise Platform Deployment Leadership Lead end‑to‑end deployment of complex cloud, data, and AI platforms across mostly Azure but also AWS Own deployment architecture, standards, and operational readiness for non‑prod and production environmentsServe as the senior escalation point for deployment‑related failures, instability, or performance issues DevOps & CI/CD Excellence Design, build, and optimize enterprise‑grade CI/CD pipelines for application, data, and AI workloads Establish and enforce deployment best practices including versioning, rollback strategies, and environment parityDrive automation to minimize manual deployment effort and reduce operational risk Kubernetes & Container Platforms Lead 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 standards Data & Analytics Platform Enablement Own deployment and operationalization of Databricks and Microsoft Fabric environmentsSupport enterprise data workloads including lakehouse architectures, analytics pipelines, and platform integrations Partner with data engineering teams to ensure deployments are optimized for scale, cost, and performance AI Platform Deployment Lead deployment of AI solutions using Azure OpenAI ServiceSupport environment configuration, endpoint management, security controls, and production hardening Operationalize AI workloads responsibly and securely Infrastructure as Code & Cloud Engineering Build and maintain Infrastructure as Code (IaC) using Terraform, ARM/Bicep, or CloudFormationEnsure cloud resources follow enterprise security, networking, and governance standards Optimize cloud environments for cost efficiency, performance, and reliability Security, Monitoring & Compliance Implement and enforce cloud security best practices (IAM, secrets, encryption, network isolation) Own monitoring, logging, and alerting strategy across deployed platforms Support audits, compliance reviews, and production readiness validations in regulated environmentsRequired Technical Skills 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 understanding Tooling & Technologies CI/CD platforms (Azure DevOps, GitHub Actions, Jenkins, or equivalent)Infrastructure as Code: Terraform, ARM templates, Bicep, CloudFormation Containers & orchestration: Docker,Kubernetes Monitoring & observability: Azure Monitor, Log Analytics, CloudWatch, PrometheusQualifications & Experience 8+ years of experience in Cloud, DevOps, or Deployment Engineering rolesProven experience leading deployments for data, analytics, and AI platformsStrong background supporting production enterprise systems \Experience in regulated or audit‑driven environments is highly preferredAbility to operate independently and lead complex deployment initiatives end‑to‑end-Thanks & regardsAkram Khan