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Salary
≈ $40k – $111k per year (Estimated)
Location
In office (Singapore)
Employment
Full-Time

Confirmed on the employer's own hiring board on Oct 13, 2026. First seen by Alion on Aug 18, 2026.

Overview
Company
Impact
Profile match
Cygnify is a talent acquisition firm based in Singapore that provides recruiting as a subscription service, deploying managed recruiting teams with flat monthly capacity and no placement fees. It recruits for enterprises, governments and start-ups across Asia and the Middle East, running searches in Singapore, Japan, Malaysia, the Philippines, Thailand, India and the UAE for clients such as property developers and IT consulting firms. Its open roles are client positions in engineering, AI and software development, presales and sales, legal, finance, HR and service delivery.

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

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