Gateway, Kubernetes & DevOps Engineer

NTT DATA•Atlanta, GA

1d•Hybrid

About The Position

We are seeking a hands-on engineer to deploy, automate, govern, and support enterprise API and AI gateway solutions running on Kubernetes. The engineer will establish reusable deployment and security patterns, integrate gateway capabilities with cloud-native platforms, and help development teams follow enterprise gateway, security, deployment, and operational standards.

Requirements

Minimum 8 years of overall experience in DevOps, platform engineering, cloud engineering, Kubernetes engineering, API platform engineering, or related enterprise technology roles.
Minimum 3 years of hands-on experience with API gateways, ingress gateways, service proxies, or API management technologies, including routing, policy enforcement, traffic management, and production support.
Minimum 4 years of hands-on Kubernetes experience, including deployments, services, ingress or Gateway API, secrets, ConfigMaps, networking, autoscaling, and troubleshooting.
Minimum 4 years of DevOps automation experience using Git, CI/CD pipelines, Helm, Terraform, infrastructure-as-code, and automated deployment practices.
Minimum 3 years of AWS cloud experience, including hands-on work with EKS and related networking, load balancing, IAM, certificate, and observability services.
Minimum 3 years of experience implementing or supporting API security controls including OAuth 2.0, OIDC, JWT, TLS, mTLS, authentication, authorization, and secure secret/certificate management.
Minimum 2 years of experience supporting production platforms through monitoring, troubleshooting, incident response, upgrades, design reviews, technical documentation, and developer enablement.
Degree: Bachelor's degree in Computer Science, Information Technology, Engineering, or equivalent relevant work experience.

Nice To Haves

1 year of hands-on exposure to Model Context Protocol (MCP), including MCP servers, clients, tools, authentication, security, and enterprise integration patterns.
Experience with AI/LLM gateway governance, AI traffic controls, model routing, prompt/response policy enforcement, or MCP server integration.
Experience with Istio, Envoy, service mesh technologies, or Kubernetes Gateway API implementations.
Experience with Prometheus, Grafana, Splunk, OpenTelemetry, or similar observability and monitoring tools.
Experience with Azure API Management (APIM), Azure Kubernetes Service (AKS), or multi-cloud gateway environments.
Experience establishing reusable platform patterns, engineering standards, and onboarding guidance for application development teams.

Responsibilities

Deploy, configure, and support enterprise API and AI gateway solutions, including Model Context Protocol (MCP) server and tool integrations.
Build and manage gateway workloads on Kubernetes, including AWS EKS or similar managed Kubernetes platforms.
Create, maintain, and enhance CI/CD pipelines, Helm charts, Terraform modules, and GitOps-based deployment processes.
Configure ingress, services, load balancers, TLS certificates, routing, authentication, authorization, rate limits, and gateway policies.
Define reusable gateway patterns, standards, and deployment templates and guide developers in following API, AI, security, and platform engineering standards.
Perform design reviews, production troubleshooting, upgrades, monitoring, incident support, root-cause analysis, and operational documentation.
Collaborate with application, cloud, network, security, architecture, and platform teams to resolve integration and operational issues.