Role : AWS AI Platform Engineer (Agentic AI / MCP Gateway)

Years of Experience : 8 Years

Primary Skills : AWS Bedrock, MCP Gateway, Agentic AI Infrastructure, Terraform/CDK, EKS, Zero-Trust AI Security Function

Role 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.
- Robust 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.

📌 AWS AI Platform Engineer (India)
🏢 Strategic HR Solutions
📍 India