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Cygnify

Backend Developer (AI)

Posted 2 Months Ago
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In-Office
Singapore, SGP
Entry level
In-Office
Singapore, SGP
Entry level
Build and operate production backend systems powering AI features. Design inference pipelines, orchestration layers, and model service boundaries while optimizing latency, throughput, caching, batching, and streaming. Monitor reliability through logging, alerting, and incident response, and develop stable APIs for mobile, desktop, frontend, and machine learning integrations. Debug distributed systems under load and continuously improve performance based on production behavior.
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Backend Engineer, AI

Role

As a Backend Engineer, AI, you own the inference and orchestration layer that powers every AI interaction in the product. Your work sits between models and users, where latency, correctness, reliability, and cost directly impact real-world experience.

You will build and operate production systems that turn model capability into fast, stable, observable APIs used across mobile and desktop clients.

Focus

  • Build and operate backend systems that serve AI-powered features in production.

  • Design inference pipelines, orchestration layers, and service boundaries around models.

  • Own production concerns: monitoring, logging, alerting, and incident response.

  • Optimize latency and throughput across inference, caching, batching, and streaming.

Ideal Experiences

  • Strong backend engineering fundamentals in production environments.

  • Experience running high-throughput, low-latency services.

  • Familiarity with AI inference patterns (LLMs, embeddings, multimodal).

  • Comfortable debugging distributed systems under load.

  • Bias toward shipping and learning from production behavior.

Outcomes

  • Backend systems run reliably at scale, handling production AI traffic with low latency and high throughput.

  • APIs are stable, clear, and support seamless integration with frontend and ML systems.

  • Production incidents are quickly detected, diagnosed, and resolved, minimizing user impact.

  • Iterative improvements based on real usage continuously increase system performance and reliability.

Tech Stack

  • Python

  • NodeJs

  • Pytorch

  • OpenAI / Anthropic / open-source LLMs

  • SQl & noSQL

  • Kubernetes

  • Docker

HQ

Cygnify Singapore, Singapore, SGP Office

Singapore, Singapore

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