Experience
8 - 13 yrs
Job Location
Noida, India
Vacancy
1
Designation
Ai Ml Engineer
Job Type
ONSITE
Job Description
Detailed JD *(Roles and Responsibilities) 8+ years of experience in AI/ML frameworks, tools, and enterprise-scale solution development across cloud platforms. 8+ years of experience in AI/ML frameworks, tools, and enterprise-scale solution development across cloud platforms.
Deep expertise in AWS services including Bedrock, SageMaker, Lambda, API Gateway, and EKS, with hands on experience in RAG-based architectures, LLM integration, and vector databases.
Strong proficiency in Python, Terraform, Harness and Infrastructure as Code (IaC) for scalable and secure cloud deployments.
AWS Certified Solutions Architect Professional certification is highly preferred.
Proven ability to collaborate effectively with onsite teams, ensuring smooth communication, alignment, and delivery across geographies.
Solid understanding of Kubernetes (EKS), IAM policies, and security frameworks in hybrid and multi-cloud environments.
Familiarity with multi-cloud GenAI architectures, integrating AWS Bedrock, Azure OpenAI, and hybrid AI gateway solutions.
Ability to architect and implement scalable, secure, and cost-effective AI solutions using AWS PaaS/IaaS services.
Experience with observability tools like CloudWatch, Grafana, or Datadog, and working in Agile/DevOps environments with CI/CD pipelines
Deep expertise in AWS services including Bedrock, SageMaker, Lambda, API Gateway, and EKS, with hands on experience in RAG-based architectures, LLM integration, and vector databases.
Strong proficiency in Python, Terraform, Harness and Infrastructure as Code (IaC) for scalable and secure cloud deployments.
AWS Certified Solutions Architect Professional certification is highly preferred.
Proven ability to collaborate effectively with onsite teams, ensuring smooth communication, alignment, and delivery across geographies.
Solid understanding of Kubernetes (EKS), IAM policies, and security frameworks in hybrid and multi-cloud environments.
Familiarity with multi-cloud GenAI architectures, integrating AWS Bedrock, Azure OpenAI, and hybrid AI gateway solutions.
Ability to architect and implement scalable, secure, and cost-effective AI solutions using AWS PaaS/IaaS services.
Experience with observability tools like CloudWatch, Grafana, or Datadog, and working in Agile/DevOps environments with CI/CD pipelines
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