AI Backend Engineer (Fintech)

TL;DR

AI Backend Engineer (Python/Node.js): Building and operating backend systems and orchestration layers for AI-powered insurance workflows with an accent on LLM inference pipelines, latency optimization, and system reliability. Focus on designing stable service boundaries between ML components and product APIs while ensuring high availability in a distributed environment.

Location: Hybrid (Malaysia). Must be based in Malaysia.

Company

Southeast Asia's largest digital insurance platform building AI-powered products to simplify insurance and financial services for millions of users.

What you will do

• Build and operate backend systems that serve AI-powered insurance workflows in production.
• Design and implement AI orchestration layers connecting models, APIs, and business logic.
• Develop inference pipelines for LLM-based and AI-assisted automation systems.
• Optimize latency, throughput, and cost across AI services via caching, batching, and routing.
• Implement comprehensive observability including logging, metrics, tracing, and alerting.
• Collaborate with frontend, product, and ML teams to ship end-to-end features.

Requirements

• Strong backend engineering experience in production systems.
• Experience building high-throughput, low-latency services.
• Familiarity with AI systems, including LLMs, embeddings, or AI workflows.
• Proven experience with distributed systems and production debugging.
• Strong understanding of APIs, data flows, and system design principles.
• Proficiency with observability tools for monitoring and tracing.

Culture & Benefits

• Work on intelligent insurance automation systems with international impact.
• High-ownership culture with end-to-end responsibility for engineering systems.
• Collaborative environment within a global engineering organization.
• Dedicated learning and development budget for continuous growth.
• Competitive compensation package.
• Hybrid work arrangement based in Malaysia.

Hiring process

• Technical evaluation followed by 3 to 4 interviews.
• Interviews conducted via virtual meetings and/or onsite.