AWS AI Infrastructure Architect with landing zone (Remote)

Role description

AWS AI Infrastructure Architect with landing zone, Edge Cloud

Remote

Role Summary

The onshore AI Infrastructure Architect is the lead technical authority for the platform and the primary architecture interface to the Customer and AWS.

This role owns the reference architecture end to end drives key design decisions across compute GPU networking orchestration and DR and governs the single touch site blueprint through its replication across all six edge sites .

The role leads and aligns onshore and offshore engineering pods.

Key Responsibilities

Own the end to end reference architecture for the Edge Cloud AIaaS platform AWS landing zone EKS on Outposts edge GPU compute G7 NVIDIA Certified servers and the NVAIE inference stack.

Design the EKSon Outposts topology choosing local vs extended cluster patterns against disconnect behaviour IPv4 only ALBonly and self managed node constraints.

Architect the multitenant isolation model vCluster namespace RBAC pertenant KMS network segmentation and RunAI project quota.

Define the NVIDIA inference architecture NVAIE NIM microservices Dynamo serving DCGM telemetry KEDA autoscaling and the OpenAI compatible API surface.

Set and govern the orchestration boundary Rafay tenancy lifecycle GitOpscatalog vs RunAI GPU scheduling vs KEDA replica autoscaling avoiding overlapping scaling control.

Architect HADR warm standby paired sites crossregion EKS controlplane resiliency secretscertconfig replication Outpost re enrolment recovery and RTORPO tiers.

Define the networking architecture IPv4first addressing designed for later IPv6 introduction Direct Connect Transit Gateway and the Local Gateway responsibility boundary.

Own the singletouch codified sitebootstrap blueprint Rafay NVAIE RunAI as code that enables replication across all six sites.

Establish the security architecture image signing Cosign SBOM Syft Wiz scanning gates and policy as code.

Provide architecture governance review IaC and designs guide engineering pods and manage architecture risks and priced assumptions.

Must Have Skills Experience

12 years in IT with 5 years in cloud platform architecture on AWS at production scale.

Deep AWS Outposts EKS VPCnetworking Direct Connect Transit Gateway KMS IAM and multiaccount landing zone Control Tower.

Strong Kubernetes architecture including multitenancy and handson understanding of EKSonOutposts constraints.

GPU AI infrastructure architecture NVIDIA GPUs GPU sharing MIG vs fractional GPU and GPU scheduling.

HADR architecture warm standby multiregion resiliency defined RTORPO tiers.

Infrastructure as Code Terraform and GitOps operating models.

Strong customerhandling skills able to run architecture workshops and design reviews with the Customer and AWS present and defend design decisions to senior stakeholders manage expectations and translate business requirements into technical solutions.

Stakeholder management and executive communication building trust with the Customer handling escalations and driving consensus across Customer AWS and LTM teams

AWS Certified Solutions Architect Professional or equivalent depth

NicetoHave Skills

Rafay or Spectro Cloud RunAI and the NVIDIA Dynamo NIM NVAIE stack

Telco edge 5G MEC platforms

SageMaker training runtime data lake Lake Formation Glue

vCluster and policyascode OPA Kyverno

Skills

Mandatory Skills : AWS Cloud Architecture

Other details

Variable Compensation: This position includes a bonus or variable payout component based on individual and organizational performance. Actual compensation within the range will be dependent upon the individual’s skills, experience, performance and internal equity.

Benefits/perks listed below may vary depending on the nature of your employment with LTIMindtree (“LTIM”):

Benefits and Perks:

• Comprehensive Medical Plan Covering Medical, Dental, Vision
• Short Term and Long-Term Disability Coverage
• 401(k) Plan with Company match
• Life Insurance
• Vacation Time, Sick Leave, Paid Holidays
• Paid Paternity and Maternity Leave

The range displayed on each job posting reflects the minimum and maximum salary target for the position across all US locations. Within the range, individual pay is determined by work location and job level and additional factors including job-related skills, experience, and relevant education or training. Depending on the position offered, other forms of compensation may be provided as part of overall compensation l…