{"id":1697945,"url":"https://alion.io/job/cliply-backend-platform-engineer","title":"Backend / Platform Engineer","company":{"id":3252662,"name":"Cliply","domain":"cliply.co","url":"https://alion.io/company/cliply","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"Backend","role_family":"Backend","seniority":"middle","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Singapore"],"countries":["SG"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":5000,"max":8000,"currency":"SGD","period":"month","gross":true,"usd_annual":75000},"salary_estimate":null,"experience_years_min":4,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Amazon EC2","optional":false},{"name":"Amazon EKS","optional":false},{"name":"Amazon S3","optional":false},{"name":"Apache Kafka","optional":false},{"name":"AWS","optional":false},{"name":"CI/CD","optional":false},{"name":"Docker","optional":false},{"name":"Embeddings","optional":false},{"name":"FFmpeg","optional":false},{"name":"GCP","optional":false},{"name":"Go","optional":false},{"name":"Google GKE","optional":false},{"name":"Grafana","optional":false},{"name":"gRPC","optional":false},{"name":"HPC","optional":false},{"name":"Java","optional":false},{"name":"Kubernetes","optional":false},{"name":"Multimodal AI","optional":false},{"name":"Node JS","optional":false},{"name":"OpenTelemetry","optional":false},{"name":"Prometheus","optional":false},{"name":"Python","optional":false},{"name":"RabbitMQ","optional":false},{"name":"Rest API","optional":false},{"name":"TorchServe","optional":false},{"name":"Triton","optional":false},{"name":"TypeScript","optional":false},{"name":"VLM","optional":false},{"name":"C","optional":true},{"name":"JavaScript","optional":true}],"status":"live","first_seen_at":"2026-10-02T00:00:00Z","employer_posted_date":null,"last_verified_at":"2026-10-02T00:00:00Z","board_verified":false,"closed_at":null,"days_open":16,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":16},"description":"Role Overview\nCliply 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.\nYou 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.\nKey Responsibilities\nMedia & AI PipelineEngineering\nBuild ingestion pipelines for long‑form video, audio and transcripts (multi‑hour content).\nDesign distributed processing workflows for frame extraction, audio segmentation and metadata generation.\nImplement asynchronous job orchestration for long‑running tasks (video processing, multimodal alignment, inference batching).\nIntegrate GPU‑backed model‑serving endpoints (LLMs, VLMs, perception models) via REST/gRPC.\nBuild caching, batching and scheduling layers for high‑volume inference workloads.\nBackend Architecture &Microservices\nDesign and implement REST/gRPC APIs for content ingestion, retrieval, metadata access and response‑tree execution.\nBuild microservices that orchestrate multimodal pipelines, queues and background workers.\nImplement robust retry logic, backpressure handling and distributed task management.\nDevelop scalable storage layers for embeddings, metadata graphs, timelines and multimodal outputs.\nCloud Infrastructure &Deployment\nArchitect and operate cloud environments (AWS/GCP) for development, staging and production.\nDeploy containerised services using Kubernetes (EKS/GKE) for microservices and model serving.\nImplement CI/CD pipelines for backend and ML components, including automated tests and blue‑green deployments.\nManage object storage (S3/GCS) for large media assets and multimodal datasets.\nObservability, Reliability& Security\nImplement monitoring, logging and tracing for long‑running pipelines and inference services.\nBuild dashboards for pipeline health, throughput, latency and failure analysis.\nEnsure security best practices across authentication, authorisation, rate limiting and usage tracking.\nConduct performance tuning for high‑throughput, low‑latency workloads.\nCollaboration & SystemDesign\nWork closely with AI/ML engineers to integrate perception and multimodal models into backend workflows.\nCollaborate with frontend engineers to expose APIs and support creative‑workflow features.\nParticipate in architecture reviews, design discussions and technical roadmap planning.\nRequirements\nMust‑Have\n4–7+ years of experience in backend, platform or distributed systems engineering.\nStrong proficiency in Python, Go, Java or Node.js/TypeScript.\nExperience with microservices, REST/gRPC APIs and asynchronous processing.\nHands‑on experience with distributed queues (Kafka, RabbitMQ, SQS, Pub/Sub).\nExperience deploying services on AWS or GCP (EKS/GKE, EC2/Compute Engine, S3/GCS).\nStrong understanding of scalability, reliability, concurrency and fault‑tolerance.\nExperience with Docker, Kubernetes and CI/CD pipelines.\nFamiliarity with large object storage and high‑volume data pipelines.\nNice‑to‑Have\nExperience integrating ML model‑serving frameworks (Triton, TorchServe, custom gRPC).\nExperience with GPU scheduling, inference batching or multimodal pipelines.\nExperience with media processing (FFmpeg, video/audio extraction, streaming APIs).\nExperience with observability stacks (Prometheus, Grafana, OpenTelemetry).\nCloud certifications (AWS/GCP) or prior experience with high‑throughput systems.\nWhy Cliply\nBuild the core engine of a next‑generation multimodal AI platform for the media industry.\nWork directly with senior AI engineers on perception, multimodal alignment and long‑form reasoning.\nSolve complex distributed‑systems challenges at the intersection of media, AI and cloud infrastructure.\nJoin a pre‑seed team where your work directly shapes the product, architecture and future of the company.\nSkills\nEndpoint Management, Platform Management, Microsoft Message Queue, Video Creation, Microservices Design, Workflow Orchestration, Fault Tolerance, High Performance Computing, Cloud Services, Rest Apis, Microservice, Docker, GCP, Java, Docker Container, Audio 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