AWS Cloud Architect

Hello Everyone,

Hope you are doing good!!!!

My name is Pavan and I work with SPAR Information System., I have a great opportunity for you, please find the job details below, if you are interested in applying please send me your updated resume and best time for you to discuss about this opportunity in details.

Role: AWS Cloud Architect

Location: Norfolk, VA -

Duration: Long term contract

Client Job Description:

Must Have Skills
Skill 1 AWS Cloud Architecture (VPC, EC2, EKS/ECS, S3, IAM, RDS, networking, security)
Skill 2 Hybrid Cloud & Network Design (VPC segmentation, routing, firewall, private connectivity)
Skill 3 Digital Experience (DX) Architecture (Web, Mobile, API, Integration platforms)
Skill 4 Infrastructure as Code (Terraform, CloudFormation) & CI/CD pipelines
Skill 5 AI/ML Architecture on AWS (model deployment, inference endpoints, data ingestion)
Skill 6 DevOps & MLOps (automation, environment patterns, model lifecycle management)
Skill 7 Security & Compliance (IAM, least privilege, secure APIs, data protection)
Skill 8 Observability & Operations (monitoring, logging, availability, incident response, model drift)
________________________________________
Domain Experience (If any)
Enterprise Digital Platforms
Cloud Transformation & Modernization
AI enabled Customer Experience / Intelligent Automation
________________________________________
Must Have Certifications
AWS Certified Solutions Architect Associate or Professional (Mandatory)
AWS Certified Security or Machine Learning Specialty (Preferred)

Job Description: Cloud, Digital Experience (DX), and AI Architecture Lead

Role Overview

Design, implement, and govern target state AWS cloud, hybrid, and AI enabled architectures for enterprise and Digital Experience (DX) applications. This role provides end to end architectural leadership across cloud infrastructure, DX platforms, and AI/ML capabilities, ensuring secure, scalable, resilient, and cost effective solutions aligned with business outcomes.

Key Responsibilities

Architecture & Solution Design

Design and maintain target state AWS cloud, hybrid, and AI enabled architectures for enterprise and Digital Experience (DX) applications, encompassing network, compute, storage, IAM, monitoring, AI/ML services, and Dev/Test/Prod environment patterns.

Define end to end Digital Experience (DX) solution architectures, including web, mobile, API, integration, and AI/ML augmentation layers such as personalization, recommendations, intelligent search, and conversational interfaces (chatbots).

Ensure architectures meet scalability, performance, resiliency, availability, and user experience requirements.

Network & Connectivity

Design AWS VPC architectures, including subnet segmentation, IP addressing, routing, firewall rules, and private connectivity.

Support secure hybrid connectivity, DX platform integrations, and AI/ML workloads, including data ingestion pipelines, real time inference, and decisioning services.

Infrastructure as Code & Automation

Develop and standardize Infrastructure as Code (IaC) patterns and CI/CD deployment pipelines.

Enable repeatable, governed deployments for:

Cloud onboarding

DX application delivery

AI/ML platform components (model deployment, inference endpoints, feature services)

Governance, Security & Compliance

Produce required architecture and onboarding artifacts, including:

Cloud Center of Excellence (CCoE) intake

Information Security intake

Data governance alignment

DevOps and MLOps readiness

Operational readiness documentation

Embed security by design across AWS, DX, and AI/ML solutions, including:

IAM role and policy design

Authentication and authorization models

Least privilege access

Secure API design

Data protection for training and inference datasets

Model access controls and sensitive data handling

AI/ML Enablement & Modernization

Assess applications and workloads to identify AI/ML enablement opportunities, such as intelligent automation, customer insights, and content personalization.

Recommend and define migration and modernization strategies, including lift and shift, rehost, refactor, and AI assisted enhancements.

Translate recommendations into implementation architectures, roadmaps, and sequencing plans.

Delivery Oversight & Execution

Provide hands on architectural oversight for end to end cloud, DX, and AI/ML initiatives.

Ensure alignment across application, API, data, and model components, addressing dependencies, data pipelines, and runtime requirements across environments.

Partner closely with platform, data, AI/ML, and delivery teams to ensure architectural intent is realized.

Operations & Run State Definition

Define and document run state and operational requirements for cloud, DX, and AI/ML workloads, including:

Availability and resiliency standards

Monitoring, logging, and observability

Model performance monitoring and drift detection

Incident response and operational baselines

Cost, Sizing & Optimization

Provide technical input for cost modeling and capacity planning, including:

Compute and storage sizing

AI/ML training and inference assumptions

Runtime usage patterns

Cost optimization strategies

Support decision making across on prem vs. cloud and traditional vs. AI enabled solution options.

Collaboration & Documentation

Coordinate with AWS platform, data, AI/ML, deployment, and DX delivery teams to define:

Build responsibilities

Prerequisites and provisioning boundaries

MLOps handoffs

Operational ownership models

Create and maintain technical deliverables, including:

Architecture and reference diagrams

Network and data flow diagrams

AI/ML reference architectures

Build guides and runbooks

Configuration baselines

Implementation standards for cloud, hybrid, DX, and AI enabled environments

Thanks & Regards,

Pavan Raikhelkar

LEAD TALENT ACQUISITION SPECIALIST

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