Artificial Intelligence Architect

• 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.

CANDIDATE SKILLS AND QUALIFICATIONS

10Years-Required-experience architecting enterprise application solutions across on-premises and cloud infrastructure

10 Years -Required-architecting solutions in one or more of the cloud platforms: GCP, Azure, and AWS.

8 Years -Required-developing cloud native application architectures across leading cloud platforms.

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

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

8 Years -Preferred-Strong understanding of virtual networks, VPNs, DNS, load balancers, and firewalls.

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

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

8 Years -Preferred-Knowledge of API design, development, and management, including RESTful and SOAP APIs.

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

8 Years -Preferred-Excellent verbal and written communication skills to articulate cloud strategies and solutions to stakeholders.

6 Years -Preferred-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.

1 Years -Preferred-Cloud Certification eg • AWS Certified Solutions Architect, Azure Solutions Architect Expert or Google Professional Cloud Architect