AI/ MLOps Engineer

DCG is a space where business needs and people's ambitions meet. They focus on well-matched collaboration, helping candidates find environments to grow and companies to build effective teams. They work closely with people and organizations, listening carefully and responding to what matters to them, creating lasting and valuable relationships.

• Minimum 5 years of professional experience as an IT Developer, MLOps Engineer, Cloud Engineer, or similar technical role.
• Very good practical knowledge of AWS SageMaker and AWS Bedrock.
• Experience working with multiple AWS services including Glue, S3, VPC, Step Functions, IAM, X-Ray, Knowledge Bases, CloudWatch, CloudTrail, Glue Catalog, SNS, EventBridge, Lambda, EC2, ECS, Fargate, KMS, MLflow, and Athena.
• Experience creating and managing AWS cloud resources using Terraform.
• Very good knowledge of cloud-native architecture and DevOps principles.
• Experience building, deploying, and operationalizing AI/ML solutions in AWS environments.
• Ability to work in complex cloud environments and support secure and scalable deployments.
• Good communication skills and ability to collaborate effectively with technical and business stakeholders.
• Fluent English language skills in speaking and writing.

• Implement MLOps, GenAI Ops, and Agentic AI Ops frameworks for AI use cases in GFCP.
• Design and configure AWS-based environments supporting AI/ML workloads.
• Work with AWS SageMaker and AWS Bedrock to enable creation, deployment, and operationalization of AI solutions.
• Create and manage cloud infrastructure using Terraform.
• Build and maintain automated processes using AWS services such as Step Functions, Lambda, EventBridge, and SNS.
• Support integration of AI/ML solutions with data services including S3, Glue, Glue Catalog, Athena, and Knowledge Bases.
• Ensure appropriate levels of security, monitoring, logging, and supervision using IAM, VPC, KMS, CloudWatch, CloudTrail, and X-Ray.
• Collaborate with technical teams and stakeholders to deliver AI functionalities aligned with program goals.
• Support scalable deployment and operational stability of AI solutions in cloud environments.