AI Backend Engineer (AI Workflow Systems)

Jobtailor; Malaysia; On-site; MYR 80,000 - 120,000; Full time

Benefits offered by this job

Learning & Development Budget

High Ownership Culture

Competitive Compensation

Hybrid Work Arrangement

Job summary

Bjak is looking for talented AI Backend Engineers to build systems that power AI-driven decisioning and automation across its platform. This hybrid role requires expertise in backend engineering, distributed systems, and collaboration with cross-functional teams. Candidates will work in a fast-paced environment focused on developing reliable AI-powered insurance products used by millions across Southeast Asia.

The ideal candidate should be comfortable debugging production systems and owning the outcome of their work. Join Bjak to innovate in the insurance industry!

Qualifications

• Strong backend engineering experience in production systems.
• Experience building or operating high-throughput, low-latency services.
• Comfortable working in fast-paced, high-ambiguity environments.

Responsibilities

• Build and operate backend systems that serve AI-powered insurance workflows.
• Optimize latency, throughput, and cost across AI services.
• Collaborate closely with frontend and ML teams to ship features.

Skills

Backend engineering experience

Strong understanding of APIs

Experience with distributed systems

Familiarity with AI systems

Observability tools experience

Tools

Python

Node.js

SQL / NoSQL databases

Kubernetes

Docker

Job description

BJAK is Southeast Asia’s largest digital insurance platform, building AI‑powered products that simplify insurance and financial services for millions of users. We use AI and automation to transform real‑world insurance workflows such as quotations, policy issuance, endorsements, claims, and customer follow‑ups.

We are looking for talented AI Backend Engineers to build the systems that power AI‑driven decisioning, automation, and orchestration across our platform. This role sits at the core of our AI stack—between models, backend systems, and real users—where latency, correctness, reliability, and cost directly impact production experience.

This is a hybrid role based in Malaysia. You will be part of a global engineering organization building AI‑powered insurance products used across Southeast Asia and beyond.

Focus

• Build and operate backend systems that serve AI‑powered insurance workflows in production.
• Design and implement AI orchestration layers that connect models, APIs, workflows, and business logic.
• Build inference pipelines for LLM‑based and AI‑assisted automation systems.
• Optimize latency, throughput, and cost across AI services (caching, batching, streaming, routing).
• Design stable service boundaries between backend systems, ML components, and product APIs.
• Implement observability: logging, metrics, tracing, alerting, and incident response workflows.
• Debug production issues across distributed AI systems and resolve root causes.
• Collaborate closely with frontend, product, operations, and ML teams to ship end‑to‑end features.
• Continuously improve system reliability, scalability, and performance.

Ideal Experience

• Strong backend engineering experience in production systems.
• Experience building or operating high‑throughput, low‑latency services.
• Familiarity with AI systems (LLMs, embeddings, or AI workflows).
• Experience with distributed systems and production debugging.
• Strong understanding of APIs, data flows, and system design principles.
• Experience with observability tools (logging, monitoring, tracing).
• Strong ownership mindset and bias toward shipping.
• Comfortable working in fast‑paced, high‑ambiguity environments.

Outcomes

• AI backend systems run reliably at scale with low latency and high availability.
• AI workflows are stable, observable, and production‑ready across multiple products.
• System performance improves continuously through real‑world feedback and optimization.
• Production incidents are quickly detected, diagnosed, and resolved.
• AI capabilities are seamlessly integrated into customer and internal workflows.

Tech Stack

• Python
• Node.js
• LLM APIs (OpenAI / Anthropic / open‑source models)
• SQL / NoSQL databases
• Kubernetes
• Docker
• Distributed systems tooling
• Observability stacks (logging, metrics, tracing)

How We Work

We believe strong products are built by small, high‑ownership teams. Engineers at BJAK work closely with product, design, AI, and operations teams to solve meaningful, real‑world insurance problems. We value technical excellence, speed of execution, and practical decision‑making. Engineers are expected to own systems end‑to‑end – from design and implementation to production reliability and iteration.

Why Join BJAK

• Build AI‑Powered Products – Work on intelligent insurance automation systems.
• Global Engineering Organization – Collaborate across multiple countries.
• International Impact – Products used by millions across Southeast Asia.
• Learning & Development Budget – Support for continuous growth.
• High Ownership Culture – End‑to‑end ownership of engineering systems.
• Modern Engineering Practices – Focus on scalability and reliability.
• Career Growth – Fast‑moving engineering environment.
• Competitive Compensation – Attractive salary package.
• Hybrid Work Arrangement – Based in Malaysia with flexible collaboration.

The Kind of Builder We Want

• Thinks in systems, not just services or endpoints
• Strong ownership of production behavior and system outcomes
• Comfortable working with ambiguity and evolving requirements
• Strong attention to failure modes, latency, and reliability
• Focused on real‑world production impact over theoretical design
• Moves fast while maintaining engineering discipline
• Obsessed with making systems stable, observable, and scalable

This Role Is Not For

• Engineers who only build features without owning production systems
• Those uncomfortable debugging distributed systems under load
• Developers who avoid responsibility for production incidents
• Engineers who require perfect specifications before starting work
• People who treat AI systems as black boxes without operational ownership