Cloud architect with AI/ML

Overview

On Site
Depends on Experience
Contract - W2
Contract - 12 month(s)
50% Travel

Skills

Excellent Verbal and Written Communication Skills
API
Application Development
Technical Requirements
Encryption
Firewalls
Containerization
Translate
Docker
Kubernetes
SOAP
Terraform
GCP
DNS
Google Cloud
PAAS
SAAS
Identity and Access Management
Articulate
Data Integrity
Cloud Security
Enterprise Application
AWS Certified
Machine Learning
Hipaa
IAAS
Enterprise Architect
Artificial Intelligence
Deep Learning
EMR
Migration Strategy

Job Details

Title: Enterprise Architect Cloud Platforms & AI/ML

Location: Austin, TX/3 Days Onsite ( Mondays, Tuesdays and Fridays )

Duration: 12+ Months

DESCRIPTION:

Must Required Certifications :

AWS Certified Solutions Architect + Azure Solutions Architect Expert or Google Professional Cloud Architect

The enterprise architect will be responsible for:

Design and maintain enterprise-level architecture that aligns with organizational goals and technical requirements.

Develop scalable, secure, and resilient enterprise infrastructure, ensuring adherence to best practice.

Evaluate current infrastructure and identify components for cloud migration, creating a detailed migration strategy including timelines and resource allocation.

Implement and validate migration processes to ensure data integrity and system functionality.

Ensure compliance of architecture with industry standards and regulatory requirements.

Collaborate with stakeholders to understand business needs and translate them into technical solutions.

Advise on AI/Machine Learning/Deep Learning and generative AI projects, mapping relevant Azure, Google, and AWS services.

Analyze AI services to extract technical and business insights that inform reference architectures, runbooks, and training content.

Minimum Requirements:

experience architecting enterprise application solutions across on-premises and cloud infrastructure

architecting solutions in one or more of the cloud platforms: Google Cloud Platform, Azure, and AWS.

developing cloud native application architectures across leading cloud platforms.

architecting solutions that utilize fit-for-purpose service models such as IaaS, PaaS, and SaaS

experience in all phases of Machine Learning, Artificial Intelligence and Deep Learning solutions using Azure or AWS or google technologies.

Strong understanding of virtual networks, VPNs, DNS, load balancers, and firewalls.

Understanding of cloud security frameworks, encryption, identity and access management (IAM), and compliance standards like GDPR, HIPAA, etc.

Familiarity with CI/CD pipelines, containerization (Docker, Kubernetes), and infrastructure as code (IaC) tools like Terraform or CloudFormation.

Knowledge of API design, development, and management, including RESTful and SOAP APIs.

Knowledge of microservices, serverless architectures, and cloud-native application development.

Excellent verbal and written communication skills to articulate cloud strategies and solutions to stakeholders.

Experience with cloud-based AI/ML services. Examples are Azure Machine Learning, Cognitive Services or AWS SageMaker, Redshift, EC2, Data Pipeline, Kinesis, EMR, Transcribe or Google Cloud Vertex AI, Agent Builder and other AI/ML services.

Cloud Certification

AWS Certified Solutions Architect, Azure Solutions Architect Expert or Google Professional Cloud Architect

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