Job Title: Enterprise Architect/Solutions Architect
Location : Austin, TX (Hybrid)
Duration : Long Term
Job Description
10 Required experience architecting enterprise application solutions across on-premises and cloud infrastructure
10 Required architecting solutions in one or more of the cloud platforms: Google Cloud Platform, Azure, and AWS.
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.
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.
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 Eg AWS Certified Solutions Architect, Azure Solutions Architect Expert or Google Professional Cloud Architect
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