Cloud Engineer

**About Marvedge ** Marvedge is an AI-powered SaaS platform that transforms how SaaS teams create and share product demo videos. With built-in screen recording, intelligent focus zooming, automated voiceovers, AI integrations, and real-time engagement analytics, Marvedge enables creators to produce polished demo videos 5 faster. **Role Overview** We are looking for a Cloud Engineer to design, build, and scale the cloud infrastructure supporting our AI-driven video processing and voiceover generation engine. You will play a pivotal role in optimizing media storage pipelines, managing serverless/containerized video rendering workloads (FFmpeg), and deploying scalable AI features. **Key Responsibilities** ● Cloud Infrastructure & Architecture: Design, deploy, and maintain scalable, secure cloud infrastructure on AWS/GCP using Terraform or Infrastructure as Code (IaC). ● Media Processing & Pipelines: Architect and optimize asynchronous queues and background workers (e.g., BullMQ, FFmpeg) for high-throughput video processing, transcoding, and rendering. ● Storage & CDN Optimization: Manage S3/Cloudflare R2 object storage, lifecycle policies, and CDN distribution for fast, global video delivery. ● AI Feature Deployment: Build robust backend and cloud infrastructure to serve AI models, voiceover generation(TTS) and automated captioning workflows. ● DevOps & CI/CD: Establish automated CI/CD pipelines, container orchestration (Docker/Kubernetes), and environment management for rapid development cycles. ● Monitoring & Security: Implement logging, metrics, and alerting (Prometheus, Grafana, Sentry) while ensuring security best practices, access control, and cost optimization. **Requirements & Qualifications** ● Experience: 1-4+years of professional experience in Cloud Engineering, DevOps, or Infrastructure. ● Cloud Platforms: Hands-on expertise with AWS (EC2, S3, ECS/EKS, Lambda, CloudFront) or GCP. ● Containers & Orchestration: Strong proficiency with Docker, container management, and serverless architectures. ● Media Handling: Familiarity with video processing pipelines, FFmpeg, background worker queues, and object storage. ● Tools & Languages: Experience with Terraform/Pulumi, Python, Node.jS / TypeScript, and CI/CD tools (GitHub Actions, Jenkins). ● Mindset: Strong problem-solving skills, ownership mindset, and enthusiasm for fast-paced SaaS startup environments. **Preferred Qualifications** ● Experience with AI/ML model deployment (LLMs, TTS engines like ElevenLabs/Whisper). ● Familiarity with HLS/DASH video streaming protocols. **Application & Next Steps** Interested candidates are invited to submit their resume, portfolio, or GitHub profile. Qualified candidates will be scheduled for an initial technical screening with the engineering lead.