Enterprise Architect 3

ENTERPRISE ARCHITECT 3

Responsibilities :

• 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.

Skills Needed : REQUIRED EXPERIENCE

10 Years

• Experience architecting enterprise application solutions across on-premises and cloud infrastructure.
• Architecting solutions in one or more of the cloud platforms : GCP, Azure, and AWS.

8 Years

• 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.

PREFERRED EXPERIENCE :

8 Years

• 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.

6 Years

• 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

• Cloud Certification eg, AWS Certified Solutions Architect, Azure Solutions Architect Expert or Google Professional Cloud Architect.