5 дней назад
Senior Principal Backend Development Engineer (AI)
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Senior Principal Backend Development Engineer (AI) (Go/Java, Distributed Systems): Designing and delivering company-wide backend initiatives, high-concurrency distributed architectures, and AI capabilities for code review, observability, and operations automation with an accent on system performance, reliability, and practical LLM engineering. Focus on solving complex cross-business technical challenges, analyzing bottlenecks and anomalies, and standardizing AI-assisted engineering practices.
Location: Kuala Lumpur, Malaysia
Company
is a cryptocurrency exchange and digital financial platform serving users across more than 200 countries and regions, with products spanning trading, payments, wealth management, custody, institutional services, and Web3.
What you will do
- Own the end-to-end technical design and delivery of company-wide engineering initiatives.
- Lead implementation of AI-assisted development, AI code review, observability analysis, and operations automation.
- Design and optimize high-concurrency distributed system architectures.
- Apply AI to capacity planning, performance bottleneck analysis, and anomaly detection.
- Resolve complex technical challenges across business lines and improve engineering efficiency and quality.
- Provide technical support and training to business teams to promote standardized AI and engineering practices.
Requirements
- 3+ years of relevant development experience and a bachelor's degree or above.
- Strong concurrent programming skills in Go or Java, with experience designing and optimizing high-concurrency systems.
- Hands-on experience with distributed services, distributed storage, and microservices architecture.
- Strong Linux knowledge and familiarity with middleware such as etcd, Nacos, and Kafka.
- Proficiency with gRPC, profiling tools, Arthas, and the Linux command line.
- Understanding of LLM fundamentals, practical AI engineering use cases, and the architectural impact of AI on stability, security, cost, and compliance.
Nice to have
- Experience with AI-assisted development or code review tools such as Copilot, Claude, or DeepSeek.
- Experience applying AI to log analysis, distributed tracing, performance profiling, anomaly detection, RAG, or internal-data tooling.
- Open-source contributions, technical blogging, or knowledge sharing.
- Experience with financial, trading, or high-availability systems.
- Knowledge of Redis, Kafka, microservices governance, service discovery, configuration management, or AI-driven operations.
Culture & Benefits
- Study Growth Fund supporting professional development and continuous learning.
- Regular team-building activities, workshops, and internal events.
- Collaboration with an international team.
- Career advancement opportunities and internal mobility.
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