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About the Role

We are seeking a motivated and detail-oriented Junior DevOps / Cloud Engineer to join our infrastructure team that we plan to grow from UK to Singapore. You’ll support the development, deployment, and monitoring of our cloud-based data pipelines, containerized environments, and ML workflows built primarily on AWS. This role is ideal for someone who’s passionate about automation, observability, and scalable system design.

Key Responsibilities

You will support senior engineers and gain experience across the following:

• Data Ingestion & Processing : Maintain and monitor AWS S3, SQS, Lambda, and EventBridge workflows for data ingestion. Help troubleshoot file processing pipelines and dead letter queues.

• Workflow Orchestration : Support and monitor Amazon MWAA (Managed Workflows for Apache Airflow) deployments. Assist with DAG versioning, checkpointing, and parameter updates stored in S3 and protected by KMS.

• Containerized Workloads : Assist with managing tasks on AWS Batch, ECS, and Fargate inside secure VPCs and subnets.

• AI & ML Services : Support integrations with Amazon services (e.g. Bedrock) and fine-tuning access between LLM services and other pipelines.

• Data Storage : Learn and maintain access policies across DynamoDB, S3, DocumentDB, Redshift, and RDS.

• Monitoring & Alerts : Work with CloudWatch, SNS, SQS, and Lambda to route alerts to Slack or Teams. Assist with building meaningful alerts and dashboards.

• CI/CD & Container Management : Support container lifecycle management using ECR, GitHub Actions, CodeCommit, CodeBuild, and CodePipeline.

Requirements

• Basic experience with AWS services (personal projects, coursework, or internship).
• Understanding of cloud-native data pipelines and APIs.
• Familiarity with Git and CI/CD principles.

Nice to Have

• Exposure to Airflow, Docker, or container orchestration tools.
• Understanding of message queues like SQS or event-based architecture.
• Interest or coursework in AI/ML systems.

What You’ll Gain

• Hands-on experience across real-time and batch data infrastructure.
• Exposure to enterprise-grade LLM applications.
• Mentorship from experienced cloud and ML engineers.

Opportunity to grow into a senior DevOps or MLOps engineer role.

To Apply

Send your CV and a short cover note to [email protected] explaining your interest in DevOps and cloud engineering.