Software Engineer, AI Infrastructure

岗位职责 / Responsibilities

Team Introduction

Our team is dedicated to building a highly available and scalable general-purpose Serverless platform that embodies the philosophy of Function-as-a-Service (FaaS). By enabling one-click function creation and deployment while abstracting infrastructure and operational complexities, we significantly reduce developers' burdens in both development and maintenance. Leveraging lightweight function execution and rapid startup capabilities, our platform dynamically scales functions to optimize resource utilization and costs. Currently handling 100M+ QPS, our architecture and product scale are industry-leading. We seek innovative, passionate engineers with experience in high-availability systems to join us in pioneering the future of serverless computing.

Responsibilities:

- Develop AI Agent Ecosystems: Contribute to designing and building AI agent frameworks, tool integration systems, and multi-agent collaboration platforms.

- Design Secure Sandbox Infrastructure: Lead the development of sandbox technologies to support secure and efficient large model inference and training workloads.

- Enhance Serverless Platform: Drive the design and evolution of our FaaS platform, focusing on usability, scalability, and cost optimization for enterprise users.

- Build Global High-Availability Architecture: Architect automated disaster recovery and fault tolerance mechanisms across multi-cluster and multi-region environments to achieve NoOps capabilities.

- Optimize Cold Start Performance: Innovate solutions for large-scale cold start scenarios, delivering multi-layered optimization to meet the demanding requirements of serverless functions.

任职要求 / Requirements

Minimum Qualifications:

- Strong Programming Fundamentals: Proficiency in algorithms, data structures, and at least one programming language (Go, Python, Java, Node.js, Rust, C).

- Distributed Systems Expertise: Hands-on experience with large-scale distributed systems, including system modeling and problem-solving in production environments.

- Cloud Native Experience: Familiarity with Kubernetes, Knative, Firecracker, or similar open-source projects.

- Serverless Product Knowledge: Experience with AWS Lambda, Google Cloud Functions, or equivalent platforms.

Preferred Qualifications:

- Familiarity with containerization, networking, and distributed tracing.

If you're passionate about pushing the boundaries of serverless computing and thrive in fast-paced, innovative environments, we want to hear from you!