Job Description

The Agentic Ops US team focuses on two major areas: Code Graph and Quality Validation. The code graph serves as the data foundation for validation, encompassing static relationships (function calls, experiment/instrumentation dependencies) and dynamic execution paths (reconstructed from traces). Quality validation covers static rule checking (mining soft and logical constraints) and dynamic issue detection, reproduction, and fixing. We aim to improve code reliability and R&D efficiency through systematic, data-driven approaches.

Responsibilities

• Design, develop, and optimize Code Graph capabilities, including static relationship extraction, dynamic trace processing, execution path reconstruction, and graph data modeling.
• Design and develop static validation capabilities based on the code graph, including mining and validating logical and soft constraints, while continuously improving rule accuracy and coverage.
• Contribute to the development of dynamic validation systems for production issue detection, reproduction, root cause localization, and assisted fixing, and build reusable solutions for common scenarios.
• Conduct in-depth analysis of complex production quality issues, leveraging code, traces, and other runtime signals to identify root causes, distill reusable validation patterns, and drive automation coverage.
• Explore and introduce cutting-edge techniques in code analysis, program slicing, anomaly detection, LLMs/Agents, and related areas, and apply them to real-world engineering problems.
• Collaborate closely with engineering and infrastructure teams to drive the adoption of Code Graph and Quality Validation capabilities in real development workflows and production scenarios.

Minimum Qualification(s)

• Bachelor's degree or above in Computer Science, Software Engineering, Artificial Intelligence, or a related field, with 3+ years of professional software development experience.
• Strong programming fundamentals and proficiency in at least one mainstream language (Go / Python / Java / C++), with solid coding practices and engineering skills.
• Strong foundation in data structures and algorithms, with the ability to analyze and abstract complex problems and independently design and implement moderately complex modules.
• Hands-on experience delivering production software projects, with the ability to independently drive requirements analysis, technical design, development, testing, and launch. Good understanding of system maintainability, reliability, and scalability.
• Strong problem-solving and investigative mindset: curious about unfamiliar problems, comfortable learning from papers, technical documentation, and source code, and able to turn fundamental insights into practical solutions.
• Strong learning agility, with the ability to quickly understand new technical domains and complex systems, proactively track technology evolution, and apply appropriate technologies to real-world problems.
• Strong communication and collaboration skills, with the ability to work effectively across teams to deliver complex technical projects.

Preferred Qualification(s)

• Experience with static analysis (e.g., AST, CFG, Call Graph, Data Flow / Pointer Analysis), program analysis, or compiler development.
• Experience with dynamic tracing, observability, or production diagnostics, such as eBPF, OpenTelemetry, or distributed tracing.
• Experience with Code Intelligence, Developer Infrastructure, automated testing, quality platforms, or Root Cause Analysis.
• Experience building large-scale distributed systems, graph processing systems, search/indexing infrastructure, or related platforms.
• Experience with LLMs, AI Coding Agents, Agentic Workflows, or AI for Software Engineering.
• Publications in academic conferences or journals related to code analysis, software engineering, or system reliability, or significant contributions to major open-source projects.