Senior AI Engineering Architect, Core Business Engineering at Coupang

Singapore, , Singapore -

Full Time

Start Date

Immediate

Expiry Date

26 Aug, 26

Salary

0.0

Posted On

28 May, 26

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

AI Architecture, LLMs, Generative AI, MLOps, PyTorch, TensorFlow, Distributed Systems, Microservices, Prompt Engineering, RAG, Kubernetes, Docker, Java, Go, Cloud Platforms, Model Fine-tuning

Industry

Software Development

Description

Please complete the attached Internal Transfer Request Form and submit. Please make sure to apply with your Coupang e-mail address. ------------------------------------------------------------------------------------------------------------------------------------------ About the Company We exist to wow our customers. We know we’re doing the right thing when we hear our customers say, “How did I ever live without Coupang?” Born out of an obsession to make shopping, eating, and living easier than ever, we’re collectively disrupting the multi-billion-dollar commerce industry from the ground up. We are one of the fastest-growing retail companies that established an unparalleled reputation for being a leading and reliable force in South Korean commerce. We are proud to have the best of both worlds — a startup culture with the resources of a large global public company. This fuels us to continue our growth and launch new services at the speed we have been since our inception. We are all entrepreneurial, surrounded by opportunities to drive new initiatives and innovations. At our core, we are bold and ambitious people that like to get our hands dirty and make a hands-on impact. At Coupang, you will see yourself, your colleagues, your team, and the company grow every day. Our mission to build the future of commerce is real. We push the boundaries of what’s possible to solve problems and break traditional tradeoffs. Join Coupang now to create an epic experience in this always-on, high-tech, and hyper-connected world Job Description This role is critical to breaking through the bottleneck in our AI development lifecycle, ensuring we can effectively scale AI capabilities and maximize the ROI of our existing AI talent and infrastructure investments. As a seasoned AI architect with deep expertise in e-commerce, you will be more than a technical executor — you will serve as the "chief translator" and "lead designer" bridging cutting-edge AI capabilities with complex e-commerce business scenarios. In this role, your core mission is to transform cutting-edge technologies — including Large Language Models (LLMs), AIGC (Generative AI), and intelligent Agents — into systematic capabilities that directly drive GMV (Gross Merchandise Volume), user experience, and operational efficiency. As a senior architect, your work spans the full spectrum from strategic planning to engineering execution: Responsibilities Technology Roadmap: Define the 3–5 year technical architecture vision for e-commerce AI. For example, deciding whether to build a proprietary large model foundation or adopt a "base model + fine-tuning" strategy; determining how to build multi-modal capabilities to handle product images, video, and live streaming. Scenario-Based Implementation: Identify the stages in the e-commerce funnel that most need AI — such as intelligent shopping guidance (solving the "users don't know what to buy" problem), AIGC content generation (auto-generating product descriptions, marketing copy, and even virtual model imagery), and supply chain intelligent forecasting. Complex System Architecture Design & Engineering Integration: This is the most critical hands-on challenge. You will need to package AI models into highly available microservices and seamlessly integrate them with existing Java/Go e-commerce tech stacks (e.g., Spring Cloud, Dubbo). AI Strategy & Feasibility Analysis: Partner with product owners and business stakeholders to translate customer needs into well-defined machine learning problems. Model Selection Expertise: Serve as the principal expert on model selection. Conduct in-depth analysis and recommend the best-fit models for each task — including leveraging internal models, fine-tuning state-of-the-art open-source models (e.g., LLMs, diffusion models), or designing entirely new architectures from scratch. Exploration & Rapid Prototyping: Lead the exploration and rapid prototyping phase to validate hypotheses and de-risk new projects before committing to full-scale development. End-to-End ML System Design & AI Infrastructure: Design complete machine learning systems, including data ingestion pipelines, prompt engineering, model training/fine-tuning workflows, and scalable serving solutions. Build the MLOps infrastructure to enable continuous integration and continuous deployment (CI/CD) for models — making training, evaluation, deployment, monitoring, and rollback as seamless as shipping regular code. Basic Qualifications Master's or Ph.D. in Computer Science, Software Engineering, Artificial Intelligence, or a related field. 10+ years of software development experience, with 3+ years in AI/ML engineering or architecture, and a proven track record of building and deploying large-scale, production-grade AI systems. Proficiency in mainstream deep learning frameworks (e.g., TensorFlow, PyTorch). Familiarity with distributed systems principles and design patterns, with experience in large-scale data processing (e.g., Hadoop, Spark, Flink). Experience with cloud platforms (e.g., AWS, Azure, GCP) and their AI/ML services. AI Technical Depth — Understanding of LLMs, RAG (Retrieval-Augmented Generation), Agents, and diffusion model fundamentals. Knowledge of prompt engineering and fine-tuning techniques. Engineering Architecture Expertise — Proficiency in distributed architecture, microservices, and containerization (Docker/K8s). Familiarity with GPU resource scheduling and optimization. Cross-Team Collaboration & Technical Leadership — Experience working with data science teams to productionize experimental models. Mentoring and developing junior and mid-level engineers to elevate overall team capabilities. Effective communication with product and business teams to understand requirements and translate them into technical solutions. Preferred Qualifications Experience with LLM training, fine-tuning, and inference optimization. Experience building MLOps platforms. Experience with edge computing or IoT AI applications. Publications at top-tier conferences (e.g., NeurIPS, ICML, CVPR). Open-source project contributions. Recruitment Process and Others Recruitment Process Application Review - Phone Interview - Onsite (or Virtual Onsite) Interview – Offer The exact nature of the recruitment process may vary according to the specific job and may be changed due to scheduling or other circumstances. Interview schedules and the results will be informed to the applicant via the e-mail address submitted at the application stage. Details to Consider This job posting may be closed prior to the stated end date for application if all openings are filled. Coupang has the right to rescind an offer of employment if a candidate is found to have submitted false information as part of the application process. Those eligible for employment protection (recipients of veteran’s benefits, the disabled, etc.) may receive preferential treatment for employment in accordance with applicable laws. Job titles and responsibilities may be subject to change depending on the candidate’s overall experience, etc. This will be communicated to the candidate at the appropriate time before the offer. Hiring may be restricted in case the legal qualifications required for hiring and work performance is not met. Privacy Notice Your personal information will be collected and managed by Coupang as stated in the Application Privacy Notice located below. https://privacy.coupang.com/en/land/jobs/ ------------------------------------------------------------------------------------------------------------------------------------------ Please complete the attached Internal Transfer Request Form and submit. Please make sure to apply with your Coupang e-mail address.

Responsibilities

Define the long-term technical architecture for e-commerce AI and translate business needs into scalable AI capabilities. Lead the design and integration of AI models into production-grade microservices to drive GMV and operational efficiency.