Cloud Engineer (AWS) | Social Cues (part-time)

GT was founded in 2019 by a former Apple, Nest, and Google executive. GT’s mission is to connect the world’s best talent with product careers offered by high-growth companies in the UK, USA, Canada, Germany, and the Netherlands.

On behalf of Social Cues, GT is looking for a Cloud Engineer with expertise in AWS.

About The Project

We’re building Social Cues Killer Prototype — an intelligent system that reimagines the traditional Killer Pool game by automating scoring and enhancing spectator engagement through edge vision and cloud-based video processing.

This phase focuses on a Proof of Concept (PoC): a minimal, reliable, end-to-end demo proving the system’s core functionality before full-scale development.

You’ll be the key engineer designing and deploying the AWS cloud infrastructure that powers it. As the Cloud Engineer, you’ll own the end-to-end AWS deployment of the PoC, ensuring the solution is lightweight, secure, cost-efficient, and ready for demo.

• Duration: 8 weeks (part-time, 16-20 hrs/week)

Responsibilities:

• Computer Vision Model Training and Support
• Collaborate with the Computer Vision team during the model training process.
• Help ensure the model accurately tracks gameplay and generates correct in-game events for the Proof of Concept.
• Infrastructure as Code (IaC)
• Design and deploy the entire PoC architecture using Terraform or AWS CloudFormation.
• Implement key AWS services, including Kinesis Video Streams (KVS), Rekognition Stream Processor, Kinesis Data Streams (KDS), Lambda, DynamoDB, and API Gateway.

• Pipeline Development

• Build and maintain the full event pipeline — from video ingestion via KVS, through Amazon Rekognition for object detection, into KDS, and finally consumed by the Game Engine Lambda.
• Ensure the pipeline operates efficiently with reliable event flow and low latency.

• Security And Access

• Set up Amazon Cognito for authentication and authorization.
• Secure all public endpoints with TLS/HTTPS, and apply IAM least-privilege principles across all services.

• Monitoring And Reliability

• Configure Amazon CloudWatch logging, metrics, and alerts to track the demo’s health.
• Focus on minimizing end-to-end latency and error rates, and address architectural concerns such as event ordering and idempotency within the game engine.
• Collaborate with the Computer Vision team during the model training process.
• Help ensure the model accurately tracks gameplay and generates correct in-game events for the Proof of Concept.
• Design and deploy the entire PoC architecture using Terraform or AWS CloudFormation.
• Implement key AWS services, including Kinesis Video Streams (KVS), Rekognition Stream Processor, Kinesis Data Streams (KDS), Lambda, DynamoDB, and API Gateway.
• Build and maintain the full event pipeline — from video ingestion via KVS, through Amazon Rekognition for object detection, into KDS, and finally consumed by the Game Engine Lambda.
• Ensure the pipeline operates efficiently with reliable event flow and low latency.
• Set up Amazon Cognito for authentication and authorization.
• Secure all public endpoints with TLS/HTTPS, and apply IAM least-privilege principles across all services.
• Configure Amazon CloudWatch logging, metrics, and alerts to track the demo’s health.
• Focus on minimizing end-to-end latency and error rates, and address architectural concerns such as event ordering and idempotency within the game engine.

Essential Knowledge, Skills & Experience:

• 3+ years of hands-on experience building and deploying on AWS.
• Expertise in serverless architecture: Lambda, DynamoDB, API Gateway, Kinesis (KVS/KDS), and Rekognition.
• Strong IaC skills using Terraform or AWS CDK.
• Python scripting experience for Lambda functions and automation.
• Familiarity with API Gateway (HTTP and WebSocket) for real-time communication.
• Experience with real-time streaming and ML-based services (Rekognition, SageMaker, OpenCV).
• Understanding of event-driven architectures — ordering, retries, and idempotency.
• Practical cost-optimization experience in AWS serverless environments.
• 3+ years of hands-on experience building and deploying on AWS.
• Expertise in serverless architecture: Lambda, DynamoDB, API Gateway, Kinesis (KVS/KDS), and Rekognition.
• Strong IaC skills using Terraform or AWS CDK.
• Python scripting experience for Lambda functions and automation.
• Familiarity with API Gateway (HTTP and WebSocket) for real-time communication.
• Experience with real-time streaming and ML-based services (Rekognition, SageMaker, OpenCV).
• Understanding of event-driven architectures — ordering, retries, and idempotency.
• Practical cost-optimization experience in AWS serverless environments.

Nice-To-Have

• Familiarity with Cognito for authentication and access control.

Interview Steps

1. GT interview with Recruiter

2. Technical Interview

3. Final Interview