🎁 Before you apply, rehearse this interview. Create your free WorkMundi account and get an Interview Training on HelpsYouSpeak — no cost, no card. I want my training →
Who we are At OKX, we believe that the future will be reshaped by crypto, and ultimately contribute to every individual's freedom. OKX is a leading crypto exchange, and the developer of OKX Wallet, giving millions access to crypto trading and decentralized crypto applications (dApps). OKX is also a trusted brand by hundreds of large institutions seeking access to crypto markets. We are safe and reliable, backed by our Proof of Reserves. Across our multiple offices globally, we are united by our core principles: We Before Me, Do the Right Thing, and Get Things Done. These shared values drive our culture, shape our processes, and foster a friendly, rewarding, and diverse environment for every OK-er. OKX is part of OKG, a group that brings the value of Blockchain to users around the world, through our leading products OKX, OKX Wallet, OKLink and more. About The Opportunity The company’s Anti-Fraud Team leverages advanced blockchain data and AI technologies to protect users and platforms from scams, abuse, and other fraudulent activities. The team develops innovative, scalable solutions that safeguard the integrity of digital ecosystems. The AI Engineer will be responsible for designing and implementing intelligent algorithms to analyze on-chain data, enabling the detection and prevention of fraudulent activities such as scams and reward/campaign abuse. The role requires expertise in transformer models, graph databases, and AI agents to strengthen detection capabilities. The AI Engineer will also lead the deployment of scalable AI services into production, ensuring reliable and real-time fraud detection. What You’ll Be Doing Develop and optimize machine learning models, with a focus on transformer-based architectures, tailored for fraud detection in blockchain data. Interpret and analyze on-chain data to extract meaningful features for building robust anti-fraud algorithms. Design and implement graph-based approaches using graph databases and graph query languages to identify complex fraud patterns. Build intelligent agents using LangGraph or similar frameworks to automate detection workflows and decision-making processes. Deploy and maintain AI services and models in production environments, ensuring scalability, reliability, and high performance. Collaborate with data engineers, product managers, and software engineers to integrate AI solutions into production workflows. Research and apply state-of-the-art techniques in fraud detection, blockchain analytics, and AI. Monitor model and service performance, troubleshoot issues, and implement enhancements in response to evolving fraud tactics. What We Look For In You Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, or a related field. Proven experience working with on-chain data and a strong understanding of blockchain transaction structures. Expertise in transformer models (e.g., BERT, GPT) and their practical applications. Experience with graph databases (e.g., Neo4j, Amazon Neptune) and graph query languages (e.g., Cypher, Gremlin). Hands-on experience building AI agents, preferably using LangGraph or equivalent frameworks. Demonstrated success in deploying AI/ML models and services in production environments (e.g., via REST APIs, microservices, or cloud platforms). Proficiency in Python and relevant AI/ML libraries (e.g., PyTorch, TensorFlow, Hugging Face). Nice to Haves Familiarity with blockchain ecosystems and smart contract mechanics. Knowledge of AI techniques in anomaly detection. Experience with scalable data pipelines and cloud infrastructure (e.g., AWS, GCP). Strong problem-solving abilities and critical thinking skills in fraud detection scenarios. Excellent communication skills and ability to work in a collaborative, cross-functional environment. Perks & Benefits Competitive total compensation package L&D programs and Education subsidy for employees' growth and development Various team building programs and company events Wellness and meal allowances Comprehensive healthcare schemes for employees and dependants More that we love to tell you along the process! Please note that Hong Kong is a group-level service hub, and OKX does not carry on a business of operating a virtual asset trading platform in Hong Kong. Notice: All official OKX vacancies are published on this website. While roles may appear on selected third-party platforms from time to time, information on other sites may be inaccurate or outdated. If in doubt, please apply directly through our official careers website. Information collected and processed as part of the recruitment process of any job application you choose to submit is subject to OKX 's Candidate Privacy Notice .
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.