Technical Architect AWS

The Technical Architect AWS will be responsible for designing and optimizing AWS cloud environments, ensuring seamless scalability, security, and high availability of AI-powered enterprise solutions. The role will involve leading AWS-based cloud strategies, solution architecture, infrastructure modernization, and automation for cloud-native AI and SaaS applications. You will collaborate closely with global technology leaders to build scalable, secure, and next-generation AI platforms. Key Objectives: Architect and optimize AWS cloud infrastructures for AI-powered enterprise applications. Ensure cloud security, compliance, and automation across BFSI, healthcare, manufacturing, retail, and cybersecurity industries. Lead AWS-based DevOps practices, ensuring seamless CI/CD pipelines and infrastructure as code (IaC). Improve cloud performance, scalability, and cost efficiency through optimization strategies. Key Responsibilities: AWS Cloud Architecture Solution Design Design and implement AWS-based cloud architectures to support iTCart s AI-powered solutions. Architect hybrid and multi-cloud environments, integrating AI workloads with AWS services. Ensure cloud solutions are aligned with business and compliance requirements. Develop and implement high-performance, scalable, and secure cloud architectures. AWS Infrastructure Automation Lead cloud infrastructure modernization, leveraging AWS Lambda, AWS Fargate, EC2, and microservices. Implement Infrastructure as Code (IaC) using Terraform, AWS CloudFormation, or CDK for automation. Ensure high availability, auto-scaling, and disaster recovery capabilities across cloud environments. Security, Compliance Governance Implement and enforce AWS security best practices, identity management, and role-based access controls (RBAC). Ensure compliance with GDPR, HIPAA, BFSI security standards, and regulatory requirements. Design and enforce AI governance frameworks, ensuring secure AI model deployment on AWS. AWS DevOps Continuous Integration/Continuous Deployment (CI/CD) Architect and manage CI/CD pipelines for AI and enterprise applications using AWS CodePipeline, GitHub Actions, and Jenkins. Optimize cloud-based AI/ML model deployment and inference using AWS SageMaker and AI services. Enable cloud-native AI automation, improving efficiency and reducing manual intervention. Cross-Functional Collaboration AI Integration Work closely with AI engineering, data science, and security teams to optimize AWS cloud solutions. Provide technical leadership and mentorship to cloud engineers and DevOps teams. Collaborate with business and product teams to align AWS solutions with enterprise goals. Key Performance Indicators (KPIs): Technology Cloud Performance AWS Infrastructure Optimization: Reduce cloud operating costs by 30% through optimization. Cloud Uptime Availability: Maintain 99.99% uptime for cloud-hosted AI solutions. AWS AI Model Deployment Efficiency: Reduce AI deployment time by 50%. Security Compliance Success Security Incident Prevention: Ensure zero critical security incidents on AWS platforms. Compliance Adherence: Maintain 100% compliance with BFSI, healthcare, and industry security standards. Governance Risk Management: Establish and enforce AI governance policies across cloud workloads. Cloud Automation Innovation Infrastructure as Code (IaC) Adoption: Automate 90% of cloud provisioning through Terraform or AWS CDK. CI/CD Pipeline Efficiency: Improve deployment frequency by 40% with automated pipelines. AI Model Training Deployment Speed: Reduce AI training cycles by 30% using AWS SageMaker. Mandatory Qualifications: 15+ years of experience in cloud architecture, enterprise solutions, and AI-powered cloud automation. Deep expertise in Amazon Web Services (AWS), cloud security, DevOps, and AI infrastructure. Hands-on experience with AWS Lambda, AWS Fargate, AWS SageMaker, Terraform, AWS CDK, and microservices. Strong knowledge of cloud networking, security, hybrid-cloud strategies, and distributed cloud architecture. Proven track record in optimizing cloud costs, performance, and security at an enterprise level. Optional Skills: Experience with AWS AI services, AI inference on the cloud, and real-time AI applications. Certifications: AWS Certified Solutions Architect Professional, AWS Security Specialty, or AWS DevOps Engineer Professional. Familiarity with cloud-native AI models, serverless computing, and federated learning architectures. Experience in AI-powered digital transformation across BFSI, healthcare, manufacturing, and retail industries.