Job Description
Level : SA and M.
Enterprise AI Platform Team Job Description :
The Enterprise AI Platform Team builds and maintains the secure, scalable AWS foundation for agentic AI workloads. This team owns infrastructure provisioning, gateways, security, and observability to enable self-service agent development.
Key Responsibilities :
- Provision and manage core AWS infrastructure including Bedrock Agent Core runtime and CSP AWS services
- Implement identity management with IAM, Cognito, Okta integration for enterprise SSO
- Build platform components : memory stores, policy enforcement engines, browser tooling
- Deploy and operate gateways : MCP Gateway (AgentCore/Kong), LLM Gateway (multimodel routing), Bedrock integration
- Manage containers and compute : Docker builds, ECR registries, EKS clusters, EC2 instances
- Author IaC with Terraform modules and maintain Jenkins/Terraform Enterprise CI/CD pipelines
- Set up RAG data infrastructure using PostgreSQL and Redshift
- Develop MCP server tools for APIs and browser integrations
- Enable multi-LLM support (AWS Nova, OpenAI, Anthropic Claude/Opus, Gemini)
- Implement comprehensive observability : CloudWatch, X-Ray, Splunk, New Relic dashboards and alerting
- Design platform APIs supporting REST, SOAP, GraphQL, OAuth2, streaming protocols, and A2A communication
Required Skills & Experience :
- 5+ years AWS platform engineering with Bedrock, AgentCore, EKS/ECR experience
- Expert Terraform IaC (modules, state management, AWS providers) and Jenkins pipeline development
- Deep gateway experience (Kong, MCP servers, LLM routing, rate limiting, guardrails)
- Strong observability implementation across CloudWatch/X-Ray/Splunk/New Relic stacks
- Enterprise identity patterns (IAM roles/SCPs, Cognito federation, Okta SSO)
- Distributed systems design for multi-tenant AI platforms with fault tolerance and compliance
Nice to Have :
- Previous enterprise AI platform builds (Bedrock Guardrails, AgentCore gateway deployments)
- Multi-model LLM gateway operations (model routing, cost optimization, SLAs)
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