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Solution Architect II - AI Tech Lead / AI Architect AWS Cloud Solutions

4 - 10 years

0 Lacs

kochi kerala

Posted:1 month ago| Platform: Shine logo

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Skills Required

enterprise architecture aws python enterprise architect

Work Mode

On-site

Job Type

Full Time

Job Description

Role Overview: As an experienced AI/ML Architect, your primary responsibility will be to design scalable, resilient, and secure AI/ML infrastructure on AWS. You will play a crucial role in translating business objectives into actionable AI strategies, overseeing the entire AI lifecycle, leading the development and deployment of AI/ML models, ensuring security and compliance, mentoring a team, and optimizing infrastructure and ML pipelines. Key Responsibilities: - Architect scalable, resilient, and secure AI/ML infrastructure on AWS using services like EC2, SageMaker, Bedrock, VPC, RDS, DynamoDB, and CloudWatch. - Develop Infrastructure as Code (IaC) using Terraform and automate deployments with CI/CD pipelines. - Translate business objectives into actionable AI strategies and solutions. - Oversee the entire AI lifecycle from data ingestion, model training, and evaluation to deployment and monitoring. - Lead selection and development of AI/ML models, especially for NLP, GenAI, and AIOps use cases. - Ensure data privacy, security best practices, and compliance with IAM policies, encryption standards, and regulatory frameworks. - Lead and mentor a team of cloud engineers, ML practitioners, software developers, and data analysts. - Establish robust model monitoring, ing, and feedback loops to detect drift and maintain model reliability. Qualification Required: - 10+ years of experience in IT with a minimum of 4 years in AI/ML leadership roles. - Strong hands-on experience in AWS services such as EC2, SageMaker, Bedrock, RDS, VPC, DynamoDB, and CloudWatch. - Expertise in Python for ML development and automation. - Solid understanding of Terraform, Docker, Git, and CI/CD pipelines. - Proven track record in delivering AI/ML projects into production environments. - Deep understanding of MLOps, model versioning, monitoring, and retraining pipelines. - Experience in implementing Responsible AI practices including fairness, explainability, and bias mitigation. - Knowledge of cloud security best practices and IAM role configuration. - Excellent leadership, communication, and stakeholder management skills. Additional Details: The company values a collaborative work environment and encourages cross-functional collaboration with both business and technical stakeholders. They prioritize ongoing optimization of infrastructure and ML pipelines to ensure the highest level of performance and reliability.,

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