AWS AI Platform Engineer

Role : AWS AI Platform Engineer (Agentic AI / MCP Gateway)Years of Experience : 8+ YearsPrimary Skills : AWS Bedrock, MCP Gateway, Agentic AI Infrastructure, Terraform/CDK, EKS, Zero-Trust AI Security FunctionRole Summary : We are seeking an AWS AI Platform Engineer to build and operate production-grade agentic AI infrastructure, including MCP Gateway and governed API/tool-calling capabilities on AWS. The role covers enterprise-scale infrastructure automation, AWS Bedrock-based AI platform engineering, and zero-trust AI security, including SSO/SCIM/Entra ID integration. The engineer will work with modern AI orchestration frameworks and enterprise security, risk, and governance practices to deliver reliable, compliant AI platform capabilities, ideally within a regulated industry context.Primary Skills (Must Have) : - 8+ years of experience in Cloud Engineering, Platform Engineering, DevOps, MLOps, Infrastructure Engineering, or AI Platform Engineering.- 3+ years supporting production AI / ML / Generative AI workloads on AWS.- Strong experience with Terraform, AWS CDK, Infrastructure as Code, and enterprise-scale AWS deployments.- Hands-on experience with API Gateway, routing, authentication, authorisation, rate limiting, and audit logging.- Extensive AWS security experience - IAM, secrets management, identity federation, and Zero Trust architectures.- Experience with AWS Bedrock, EKS, Lambda, API Gateway, CloudWatch, X-Ray, Docker, Helm, and CI/CD pipelines.Technical Knowledge : AI Platform & Orchestration : - MCP Gateway and tool-calling infrastructure.- AWS Bedrock, EKS, API Gateway, Lambda, IAM.- LangGraph, AutoGen, Bedrock Agents.- MLflow, Kubeflow, model registries, and MLOps practices.Infrastructure & Security : - Terraform, AWS CDK, and infrastructure automation.- OAuth 2.0, OIDC, JWT, RBAC, ABAC.- Docker, Kubernetes, Helm.Observability : - CloudWatch, X-Ray, Prometheus, Grafana, Datadog, OpenTelemetry.Governance & Delivery : - Enterprise security, risk, governance, and responsible AI practices.- Agile delivery practices.Secondary Skills (Nice to Have) : - Experience with MCP or equivalent AI tool-calling frameworks is highly desirable.- Experience in regulated industries such as Banking, Financial Services, Insurance, Healthcare, or Telecommunications is preferred.Experience & Qualifications : - 8+ years of overall experience in cloud, platform, DevOps, MLOps, or AI platform engineering.- 3+ years specifically supporting production AI/ML/GenAI workloads on AWS.- Bachelor's / Master's degree in Computer Science, Engineering, or a related field (or equivalent experience).Ways of Working : - Agile delivery within a production AI platform engineering team.- Collaboration with security, risk, and governance functions on responsible AI delivery.- Locations open across Bangalore and Pune. (ref:hirist.tech)