Binance Accelerator Program - Dev

Binance is a leading global blockchain ecosystem behind the world’s largest cryptocurrency exchange by trading volume and registered users. We are trusted by 300+ million people in 100+ countries for our industry-leading security, user fund transparency, trading engine speed, deep liquidity, and an unmatched portfolio of digital-asset products. Binance offerings range from trading and finance to education, research, payments, institutional services, Web3 features, and more. We leverage the power of digital assets and blockchain to build an inclusive financial ecosystem to advance the freedom of money and improve financial access for people around the world. About Binance Accelerator Program Binance Accelerator Program is a concise fixed-term program designed for Early Career Talent to have an immersive experience in the rapidly expanding Web3 space. You will be given the opportunity to experience life at Binance and understand what goes on behind the scenes of the worlds’ leading blockchain ecosystem. Alongside your job, there will also be a focus on networking and development, which will expand your professional network and build transferable skills to propel you forward in your career. Learn about BAP Program HERE   Who may apply  Current university students and recent graduates We are seeking a DevOps intern to support our real-time data streaming needs. The ideal candidate will have basic knowledge of Redis/Kafka and a keen interest in building and maintaining operation pipelines. This role will involve working with senior engineers to ensure our Redis/Kafka infrastructure is robust and efficient. OKR for this role: Leverage AI tools to track Redis/Kafka performance and streamline troubleshooting Key Stakeholders: Devops Engineer: Deep performance tuning, capacity planning, improve cluster stability and Mentoring, ensuring your work aligns with production standards. Devops Team: automates repetitive tasks, freeing up human resources for more strategic and creative work, accelerating the development and deployment process. Developer team: Convincing developers to trust AI-driven insights over traditional methods. Deliver Faster, Actionable Responses.

Responsibilities

Assist in the installation, configuration, and maintenance of Redis/Kafka clusters.

Monitor Redis/Kafka performance metrics and troubleshoot issues.

Support the development and maintenance of Kafka-based data pipelines.

Work with development teams to integrate Kafka into applications and Participate in debugging and resolving Kafka-related problems.

Develop and optimize Redis client libraries for applications.

Stay informed about Redis/Kafka updates and industry best practices.

Research and apply MCP methodologies with AI enhancements for Redis/Kafka optimization

Help maintain documentation for Redis/Kafka procedures and AI insights for Redis/Kafka operations and troubleshooting.

Requirements

Basic understanding of Apache Kafka and its components (brokers, topics, producers, consumers).

Basic knowledge of Linux operating systems and Programming experience in Python/Java/Golang, experience with Redis module or Kafka development is a big plus.

Familiarity with distributed systems and real-time data processing concepts.

Understanding of network protocols and data serialization formats (e.g., Avro, JSON).

Strong engineering mindset, fast learning ability, and excellent problem-solving and troubleshooting skills.

Good communication skills and ability to collaborate effectively with team members.

Eagerness to learn and grow in the field of data streaming and messaging systems.

Interest in learning and applying AI/ML techniques for Redis/Kafka performance monitoring and optimization.

Key scopes

Middleware Stability & High Availability: Assisting in maintaining high-availability Kafka/Redis clusters, despite limited production experience.

Performance Monitoring & Alert: Filtering out irrelevant alerts while accurately identifying genuine performance bottlenecks or failures.

Effective AI Model Integration: Ensuring AI tools accurately correlate Redis/Kafka metrics (e.g., latency, throughput, consumer lag) with real issues, avoiding false positives/negatives.