Agent System Backend Engineer Graduate (AML Ark) - 2027 Start

关于这个机会

Team Introduction Volcano Ark is Volcano Engine's one-stop foundation model and Agent platform for enterprises and developers. Our team is building the next-generation infrastructure for general-purpose Agents capable of handling complex tasks—from Agent runtimes and execution engines, to platform-level resource models, lifecycle management, and public APIs, as well as evaluation and observability systems. We are looking for talented individuals to join our team. As a graduate, you will get opportunities to pursue bold ideas, tackle complex challenges, and unlock limitless growth. Successful candidates must be able to commit to an onboarding date by the end of the year. Please state your availability and graduation date clearly in your resume. Candidates can apply to a maximum of two positions and will be considered for jobs in the order you apply. The application limit is applicable to our Company and its affiliates' jobs globally. Applications will be reviewed on a rolling basis - we encourage you to apply early. Responsibilities -Develop the core Agent infrastructure for the Volcano Ark platform by designing and implementing a highly reliable, scalable Agent runtime and execution engine. Improve execution efficiency, security, and stability while building a general-purpose Agent infrastructure capable of supporting complex tasks. -Build core platform capabilities, including resource model abstraction, lifecycle management, and configuration management. Integrate with the Volcano Engine Open Platform to deliver external-facing OpenAPIs, covering API registration, publishing, authentication, rate limiting, and metering & billing, ensuring reliability, compatibility, and operational stability. -Design and develop the Agent evaluation framework by integrating industry-standard benchmarks. Enable compatibility with leading Agent harnesses including **Claude Code, Codex, and OpenCode**, while building a unified integration layer and execution protocol. Develop capabilities for metrics collection, trace replay, bad-case analysis, and cost/latency analytics to continuously improve the platform. -Ensure the quality of online services under high-concurrency and large-scale workloads by building robust performance optimization, reliability, and observability capabilities across the Agent platform. -Stay at the forefront of Agent technologies and AI-native applications by exploring next-generation Agent paradigms. Drive the productization of platform capabilities to improve developer productivity, while serving as a power user of the Agent platform to continuously refine and enhance its core capabilities through real-world feedback.

任职要求

Minimum Qualifications: - Individuals who are completing or have recently completed a Bachelor's/ Master's degree in computing or a related discipline. - Solid coding skills and system design capabilities. Proficient in at least one of Golang, Python, Rust, or Java, with hands-on experience using AI-powered coding tools. - Strong understanding of large language models and Agent architectures, including key concepts such as tool calling, context management, long-horizon execution, and self-invocation. Candidates with hands-on experience building production Agent systems or extensive experience using coding agents such as Claude Code, Codex, or Cursor are preferred. - Familiar with Linux, container technologies (Docker, Kubernetes), and cloud-native infrastructure. Understanding of distributed systems, task scheduling, observability, resource isolation, and network access control. Experience with declarative APIs, the Kubernetes controller pattern, and Operator/CRD development is a plus. - Backend & Distributed Services: Experienced in microservice architecture and common backend technologies such as MySQL, Redis, and message queues. Strong API design and data modeling skills. Experience designing and optimizing high-concurrency, low-latency online services is preferred. Preferred Qualifications: - Familiar with container runtime, virtualization technologies (e.g., runC, gVisor, Kata Containers, Firecracker), serverless platforms, cloud provider PaaS, open platforms, multi-tenant systems, or large-scale data storage and retrieval systems. - Passionate about AI-native applications and staying current with the latest advancements in Agent technologies. Able to demonstrate ability to rapidly reproduce research ideas and translate them into production-ready systems.

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