What you will do (Key responsibilities)

1) Architect and deliver customer AI infrastructure (end-to-end)
Lead architecture and implementation for secure, scalable AI/ML/LLM platforms based on customer requirements and constraints.
Produce implementation-ready artifacts: HLD/LLD, reference architectures, network/topology diagrams, deployment plans, runbooks, and operational handover packs.
Translate business and technical requirements into a scalable target state, and guide delivery teams through build, rollout, and production readiness.

2) Solve real enterprise constraints (network + access + topology)
Design enterprise network topologies with segmentation/isolation: private subnets, route tables, security policies, egress control, private endpoints, controlled ingress patterns.
Work within common enterprise constraints
Fixed network address plans (pre-approved CIDR ranges), IP allowlists/deny-lists, and limited routing flexibility
Private connectivity requirements (VPN/Direct Connect/FastConnect/ExpressRoute), no public endpoints, and restricted DNS resolution




Controlled administrative access (bastion/jump host, privileged access management, session recording, time-bound access)
Restricted egress (proxy-only outbound, firewall-controlled destinations, egress allowlists, DNS filtering, no direct internet)Ensure secure data movement and integration patterns for AI workloads (east-west and north-south traffic)
Customer-managed encryption and key custody (KMS/HSM, BYOK/HYOK, key rotation, certificate lifecycle)
Strict TLS policies (mTLS, approved ciphers, enterprise PKI, certificate pinning where required)
Identity and access controls (SSO/SAML/OIDC, RBAC/ABAC, least privilege, break-glass accounts)
Data governance constraints (PII/PHI handling, residency/sovereignty, retention, audit evidence requirements)
Secure software supply chain (approved base images, artifact signing, SBOM, vulnerability scanning, patch SLAs)
Endpoint controls (E

📌 Ai Infrastructure Architect Bengaluru (India)
🏢 Oracle
📍 India