Senior Principal Backend Development Engineer
About the role
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- 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
- 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
- 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
- Bachelor's degree or above
- 3+ years of relevant development experience
- Strong communication skills and collaborative spirit
- 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
- 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
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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
Why Join Us
At Bybit, we are committed to fostering a supportive and enriching work environment.
Our benefits include:
- Study Growth Fund: We support your professional development and continuous learning.
- Internal Events: Participate in regular team-building activities, workshops, and events designed to promote collaboration and innovation.
- Global Collaboration: Be part of a diverse, international team, working alongside colleagues from around the world.
- Career Advancement: Access opportunities for growth and advancement within a rapidly expanding global company.
- Internal Mobility: Grow with us- Your long-term development is important to us. We offer internal job opportunities to help build your career path.
