Job Overview
Location
Seoul, Korea
Job Type
Full-time
Category
Software Engineering
Date Posted
June 4, 2026
Full Job Description
đź“‹ Description
- • Build end-to-end AI-native product features that transform LLM capabilities into persistent, goal-driven workflows beyond chat-based interactions.
- • Design agent workflows that handle multi-step planning, tool usage, failure recovery, and consistent state management across user sessions.
- • Integrate LLMs (OpenAI, Anthropic, open-source), retrieval-augmented generation (RAG) systems, and external tools into reliable production systems with real-world task completion as the goal.
- • Develop real-time AI interactions with streaming responses, partial result delivery, and strict latency constraints to ensure responsive user experiences.
- • Improve system reliability by implementing robust fallback mechanisms, observability layers, and recovery protocols for LLM and tool failures in production.
- • Collaborate closely with ML, backend, and product teams to ship features from concept to deployment with full ownership of the technical implementation.
- • Design and maintain scalable API architectures that connect frontend interfaces with backend services and AI model endpoints.
- • Optimize system performance by reducing latency while preserving output quality and consistency in AI-driven workflows.
- • Establish reusable patterns and abstractions for integrating memory, external tools, and LLMs into scalable, maintainable product systems.
- • Iterate on product features based on real user usage data, failure modes, and performance metrics to continuously improve success rates of AI workflows.
- • Contribute to a product experience where AI behaves proactively, consistently, and dependably over extended interactions and multi-day tasks.
- • Work with Next.js for frontend development and Node.js/Python for backend services to deliver seamless full-stack functionality.
- • Deploy and manage services using Docker and Kubernetes in a production environment with high availability and monitoring requirements.
- • Utilize SQL and NoSQL databases to store persistent context, user state, and workflow history for long-running AI agents.
- • Apply PyTorch for custom model fine-tuning or evaluation pipelines where needed to enhance system behavior.
- • Operate in a fast-moving, high-talent-density environment with evolving requirements, making pragmatic engineering decisions under ambiguity.
- • Participate in a collaborative decision-making culture that values transparency, efficiency, and independent execution with strong ownership.
- • Engage in a streamlined interview process of 3–4 virtual or onsite interviews evaluated by technical team members.
🎯 Requirements
- • Strong experience in full stack engineering (frontend + backend)
- • Solid understanding of system design and API architecture
- • Experience working with LLMs, RAG systems, or AI-powered applications
- • Ability to handle ambiguity and make pragmatic engineering decisions
- • Strong ownership — able to take features from idea to production
- • Comfort working in fast-moving environments with evolving requirements
🏖️ Benefits
- • Opportunity to build a magical AI product used by billions globally
- • Work in a high-talent-density, hands-on team with collective decision-making
- • Fast-paced environment with rapid iteration and direct impact on product
- • Streamlined interview process with prompt decisions and transparency
Skills & Technologies
Python
JavaScript
Next.js
Node.js
Docker
Full Stack
Onsite
About Bjak Sdn. Bhd.
Bjak operates Malaysia’s largest digital auto-insurance marketplace, enabling instant price comparison and online purchase of motor coverage from leading insurers. The platform uses proprietary technology to simplify complex tariffs, deliver personalised quotes and e-policy issuance within minutes, eliminating paperwork and agent visits. Licensed by Bank Negara Malaysia, Bjak also offers road-tax renewal, accident assistance and claims support, serving millions of drivers nationwide while partnering with insurers to increase digital distribution efficiency and customer reach.
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