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.
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.
Nice-to-have
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.
Familiarity with Cognito for authentication and access control.
Interview Steps
GT interview with Recruiter
Technical interview
Final interview