What You'll Do
Guide and expand a high-performing engineering team in Shanghai, ensuring alignment with broader technical goals and organizational priorities. Foster a culture of collaboration, accountability, and continuous improvement.
Oversee task planning, performance tracking, and delivery quality to meet service level expectations. Serve as the technical point of contact for escalated customer issues, coordinating with Sales, Customer Experience, and Sales Engineering to resolve complex challenges.
Conduct regular one-on-one meetings, deliver meaningful feedback, and lead performance evaluations. Address team dynamics proactively and support professional growth through coaching and development opportunities.
Collaborate with engineering leadership and cross-functional partners to set clear expectations and ensure smooth integration across teams, especially in distributed or remote environments.
Requirements
- Minimum of five years managing software engineering teams with a strong focus on customer-facing outcomes
- Proven technical depth in AI and large language models, particularly in areas such as APIs, model integration across providers, self-hosted deployments, RAG architectures, vector databases, and MCP
- Experience leading remote or geographically distributed teams
- Demonstrated ability in hiring, performance reviews, and compensation discussions
- Background in on-premise, cloud, or hybrid software solutions
- Strong interpersonal skills with stakeholders across technical and non-technical functions
- Business-level fluency in English, both written and spoken
Preferred Qualifications
- Direct experience developing and maintaining backend systems using NGINX or OpenResty
- Prior work in enterprise software environments
- Hands-on involvement in Rust-based projects
Technical Environment
AI and LLM systems, API infrastructure, multi-provider model integration, self-hosted models, retrieval-augmented generation (RAG), vector databases, MCP, NGINX, OpenResty, Rust.
Work Mode
This role is based in Shanghai and follows a local-city work model, requiring on-site presence as part of the local team structure.
