Job Opportunities API

About Us Established in 2018, Bybit is one of the world’s leading cryptocurrency exchanges and digital financial platforms, serving over 80 million users across more than 200 countries and regions. Powered by world-class technology and a user-first mindset, Bybit delivers a seamless ecosystem across trading, payments, wealth management, custody, institutional services, and Web3 — connecting users to the future of digital finance.   Our core values define how we build. We listen, care and improve to create products and experiences that put users first. Backed by a global team of ambitious builders, problem-solvers, and innovators, we foster a high-performance and fast-moving environment where talent is empowered to drive real impact at the global scale. Supported by 24/7 multilingual customer service and a strong commitment to innovation, we are shaping the future of finance through technology, collaboration, and bold execution.   Today, Bybit is recognized as one of the most trusted and transparent platforms in the digital asset industry, continuing to expand its global presence while building the infrastructure for the next generation of financial services. Responsibilities Own end-to-end technical solution design and delivery for company-wide technical initiatives Lead the engineering implementation of AI capabilities, including but not limited to AI-assisted development, AI code review, AI observability analysis, and AI-driven operations automation Proactively resolve complex technical challenges across business lines, driving improvements in efficiency and quality through technical means Design and optimize high-concurrency, distributed system architectures, and explore AI applications in capacity planning, performance bottleneck analysis, and anomaly detection Provide technical support and training to business teams, promoting the adoption and standardization of AI + engineering capabilities across the organization Requirements I. Core Engineering & Architecture Strong coding fundamentals: proficiency in Go or Java concurrent programming, with deep understanding of design and optimization in high-concurrency scenarios Distributed systems experience: hands-on experience with distributed services and distributed storage; familiarity with microservices architecture design System optimization: solid knowledge of Linux OS; understanding of middleware internals and engineering practices (e.g., etcd, Nacos, Kafka) Frameworks & protocols: proficiency in gRPC; experience with development and performance tuning is a plus Troubleshooting skills: proficient with profiling tools, Arthas, and Linux CLI for system analysis and issue diagnosis II. AI & Intelligence Engineering AI engineering mindset: understanding of LLM fundamentals, capability boundaries, and practical engineering usage Preferred — one or more of the following: Engineering experience with AI-assisted development / code review tools (e.g., Copilot, Claude, DeepSeek) Practical experience applying AI to log analysis, distributed tracing, performance profiling, or anomaly detection Design experience with AI knowledge augmentation (RAG) or tooling systems built on internal data (code, logs, metrics, docs) Ability to evaluate the impact of AI capabilities on system stability, security, cost, and compliance from an architectural perspective Clear understanding of AI's role as an "assistive tool" in engineering — avoids over-reliance and demonstrates sound engineering judgment Experience & Contributions Bachelor's degree or above; 3+ years of relevant development experience Open-source contributions, or a track record of technical blogging / knowledge sharing is a plus Strong communication and collaboration skills; ability to dri