О нас
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.
Обязанности
- Lead end-to-end technical solution design and drive implementation across the organization
- Spearhead AI engineering adoption (AI-assisted development, AI code review, AI-powered observability, AI-driven operations automation, etc.)
- Proactively resolve complex technical challenges across business lines, improving efficiency and quality through technical innovation
- Design and optimize high-concurrency, distributed system architectures; explore AI applications in capacity planning, performance bottleneck analysis, and anomaly detection
- Provide technical guidance and training to business teams, driving the adoption and standardization of AI + engineering capabilities
Требования
Must-Have
I. Core Engineering & Architecture
- Proficient in Go or Java concurrent programming with deep understanding of high-concurrency system design and optimization
- Hands-on experience with distributed services and distributed storage; familiar with microservice architecture design
- Solid knowledge of Linux OS and system-level understanding of middleware (etcd, Nacos, Kafka)
- Expert-level proficiency in gRPC framework with development and performance tuning experience
- Skilled in using profiling tools, Arthas, and Linux command-line utilities for system analysis and troubleshooting
II. AI & Intelligent Systems
- AI engineering mindset with understanding of LLM fundamentals, capability boundaries, and practical engineering applications
- Ability to evaluate AI's impact on system stability, security, cost, and compliance from an architectural perspective
- Clear understanding of AI's "assistive role" in engineering — avoiding over-reliance while leveraging its strengths
III. Experience & Education
- Bachelor's degree or above
- 3+ years of relevant development experience
- Strong communication skills and collaborative spirit
Будет плюсом
- Hands-on experience implementing AI-assisted development/code review (Copilot, Claude, DeepSeek, etc.) at the engineering team level
- Practical application of AI in log analysis, distributed tracing, performance profiling, and anomaly detection
- Design experience with AI knowledge augmentation (RAG) or tooling systems based on internal data (code, logs, metrics, documentation)
- Open-source project contributions
- Sustained technical blog or knowledge-sharing track record
Будет плюсом
- Experience designing financial systems, trading systems, or high-reliability systems
- AI-driven observability, automated operations, or stability engineering experience
- Deep familiarity with open-source middleware internals (Redis, Kafka, etc.)
- Microservice governance, service discovery, and configuration center design experience
- Proven track record in high-performance architecture design or AI engineering implementation
Core Competency Matrix
Technical Skills (High Priority): Go/Java concurrency, distributed architecture, middleware, gRPC, performance tuning
AI Engineering (High Priority): LLM understanding, AI-assisted development adoption, RAG/tooling design
Project Experience (High Priority): High-concurrency systems, distributed storage, microservice architecture
Problem Solving (High Priority): Profiling, Arthas, Linux command-line troubleshooting
Communication (Medium Priority): Technical training, cross-team alignment, solution evangelism
Industry Background (Medium Priority): Finance/trading/high-reliability systems
Role Characteristics
Core Positioning: A hybrid AI + Architecture role that requires not only traditional distributed systems expertise but emphasizes AI engineering adoption capabilities.
Key Differentiators
- Must lead AI capability implementation at the engineering level — not merely use AI tools
Must evaluate AI's impact on systems from an architectural perspective (stability, security, cost, compliance)
Must drive AI + engineering capability adoption and standardization across teams
Interview Focus Areas
Distributed Architecture: High-concurrency design, microservice architecture, middleware selection and tuning
AI Engineering: Depth of LLM understanding, AI implementation experience, awareness of AI limitations
Problem Solving: Complex troubleshooting experience, performance optimization case studies
Driving Adoption: Technical solution advocacy experience, cross-team collaboration skills…
Текст вакансии длинный, здесь показана его часть. Полностью — на сайте студии.
Отклик принимает студия на своём сайте. LOOTWORK только показывает вакансию.