Backend / Platform Engineer

CLIPLY PTE. LTD.; Singapore; On-site; SGD 120,000 - 190,000; Full time

Job summary

Cliply is building a high-throughput, multimodal AI platform that processes long-form video, audio and text to generate structured narrative intelligence for broadcasters and media companies. As a Backend / Platform Engineer, you will design and operate the distributed systems, media pipelines and model-serving infrastructure that power Cliply’s core engine.

You will collaborate with AI/ML teams to integrate perception models and inference services into a scalable production environment.

Qualifications

• 4–7+ years of backend, platform or distributed systems experience.
• Proficient in Python, Go, Java, or Node.js/TypeScript.
• Experience with microservices, REST/gRPC and async processing.
• Hands-on with distributed queues (Kafka, RabbitMQ, SQS, Pub/Sub).
• Experience deploying on AWS or GCP (EKS/GKE, EC2, S3/GCS).
• Strong understanding of scalability, reliability, concurrency and fault-tolerance.
• Experience with Docker, Kubernetes and CI/CD pipelines.
• Familiarity with large object storage and high-volume data pipelines.

Responsibilities

• Build ingestion pipelines for long-form video, audio and transcripts.
• Design distributed processing workflows for frame extraction and metadata generation.
• Implement asynchronous job orchestration for long-running tasks.
• Integrate GPU-backed model-serving endpoints via REST/gRPC.
• Build caching, batching and scheduling layers for high-volume inference workloads.
• Develop scalable storage layers for embeddings, metadata graphs, timelines and multimodal outputs.

Skills

Python

Go

Java/TypeScript

REST/gRPC APIs

Distributed systems

Docker

Kubernetes

AWS/GCP

CI/CD

Kafka/RabbitMQ

S3/GCS

Tools

Kafka

RabbitMQ

SQS

Pub/Sub

Docker

Kubernetes

EKS/GKE

S3/GCS

Job description

Role Overview

Cliply is building a high-throughput, multimodal AI platform that processeslong-form video, audio, and text to generate structured narrative intelligencefor broadcasters and media companies. As a Backend / Platform Engineer, youwill design and operate the distributed systems, media pipelines and model‑servinginfrastructure that power Cliply’s core engine.

You will work closely with AI/MLengineers to integrate perception models, multimodal alignment models andLLM/VLM inference services into a scalable production environment. This role iscritical to transforming our AI engine into a reliable, production‑readyplatform.

Key Responsibilities

Media & AI PipelineEngineering

• Build ingestion pipelines for long‑form video, audio and transcripts (multi‑hour content).
• Design distributed processing workflows for frame extraction, audio segmentation and metadata generation.
• Implement asynchronous job orchestration for long‑running tasks (video processing, multimodal alignment, inference batching).
• Integrate GPU‑backed model‑serving endpoints (LLMs, VLMs, perception models) via REST/gRPC.
• Build caching, batching and scheduling layers for high‑volume inference workloads.

Backend Architecture & Microservices

• Design and implement REST/gRPC APIs for content ingestion, retrieval, metadata access and response‑tree execution.
• Build microservices that orchestrate multimodal pipelines, queues and background workers.
• Implement robust retry logic, backpressure handling and distributed task management.
• Develop scalable storage layers for embeddings, metadata graphs, timelines and multimodal outputs.

Cloud Infrastructure & Deployment

• Architect and operate cloud environments (AWS/GCP) for development, staging and production.
• Deploy containerised services using Kubernetes (EKS/GKE) for microservices and model serving.
• Implement CI/CD pipelines for backend and ML components, including automated tests and blue‑green deployments.
• Manage object storage (S3/GCS) for large media assets and multimodal datasets.

Observability, Reliability & Security

• Implement monitoring, logging and tracing for long‑running pipelines and inference services.
• Build dashboards for pipeline health, throughput, latency and failure analysis.
• Ensure security best practices across authentication, authorisation, rate limiting and usage tracking.
• Conduct performance tuning for high‑throughput, low‑latency workloads.

Collaboration & System Design

• Work closely with AI/ML engineers to integrate perception and multimodal models into backend workflows.
• Collaborate with frontend engineers to expose APIs and support creative‑workflow features.
• Participate in architecture reviews, design discussions and technical roadmap planning.

Requirements

Must‑Have

• 4–7+ years of experience in backend, platform or distributed systems engineering.
• Strong proficiency in Python, Go, Java or Node.js/TypeScript.
• Experience with microservices, REST/gRPC APIs and asynchronous processing.
• Hands‑on experience with distributed queues (Kafka, RabbitMQ, SQS, Pub/Sub).
• Experience deploying services on AWS or GCP (EKS/GKE, EC2/Compute Engine, S3/GCS).
• Strong understanding of scalability, reliability, concurrency and fault‑tolerance.
• Experience with Docker, Kubernetes and CI/CD pipelines.
• Familiarity with large object storage and high‑volume data pipelines.

Nice‑to‑Have

• Experience integrating ML model‑serving frameworks (Triton, TorchServe, custom gRPC).
• Experience with GPU scheduling, inference batching or multimodal pipelines.
• Experience with media processing (FFmpeg, video/audio extraction, streaming APIs).
• Experience with observability stacks (Prometheus, Grafana, OpenTelemetry).
• Cloud certifications (AWS/GCP) or prior experience with high‑throughput systems.

Why Cliply

• Build the core engine of a next‑generation multimodal AI platform for the media industry.
• Work directly with senior AI engineers on perception, multimodal alignment and long‑form reasoning.
• Solve complex distributed‑systems challenges at the intersection of media, AI and cloud infrastructure.
• Join a pre‑seed team where your work directly shapes the product, architecture and future of the company.