夜雨聆风
Location: Shenzhen/Guangzhou
Team Leadership & Development: Lead, mentor, and grow a high-performing engineering team, including setting clear goals, conducting performance reviews, providing technical guidance, and fostering a culture of collaboration, innovation, and continuous improvement. Ensure the team has the resources, skills, and support needed to deliver high-quality work.
Technical Strategy & Roadmap: Define the technical vision and long-term roadmap for the AI Gateway, aligning with the bank’s AI Platform strategy and business needs. Evaluate emerging technologies, architectural patterns, and industry best practices to enhance the gateway’s scalability, security, and usability.
Design & Development Oversight: Oversee the end-to-end design, development, testing, and deployment of the AI Gateway. Ensure the gateway provides a standardized, intuitive interface for model access (e.g., REST APIs, websocket), supports model versioning, authentication/ authorization, rate limiting, monitoring, and logging, and integrates seamlessly with the bank’s existing AI models and infrastructure.
Service Reliability, Performance & Compliance: Ensure the AI Gateway operates with exceptional performance, scalability, low latency, and high throughput, especially in high-concurrency scenarios typical of enterprise banking operations. Implement robust performance monitoring, load testing, and optimization strategies to maintain service stability under peak loads. Establish incident response processes to minimize downtime, resolve performance bottlenecks promptly, and continuously optimize the gateway’s performance.
Delivery Management: Lead agile development processes, set delivery timelines, prioritize tasks, and manage dependencies to ensure on-time, high-quality delivery of gateway features and enhancements. Track project progress, communicate risks and status to stakeholders, and make data-driven decisions to adjust plans as needed.
Technical Governance: Establish and enforce engineering standards, coding practices, and quality assurance processes for the AI Gateway. Ensure code reviews, testing (unit, integration, performance), and documentation are thorough and consistent.
Education: Bachelor’s or Master’s in Computer Science, Software Engineering, or related field; equivalent experience considered.
Experience & leadership: 8+ years in software engineering, including 3+ years as a tech lead/ engineering leader on large-scale platform initiatives.
AI gateway & API gateway architecture: Hands-on AI gateway experience; strong preference for deep Kong API Gateway architecture knowledge, plus familiarity with Portkey-AI, APISIX, or Higress.
Cloud & Kubernetes: Expertise across major cloud platforms (AWS, GCP, Azure, Alibaba Cloud) and advanced enterprise Kubernetes operations (ingress strategies, optimisation for stateful/ stateless workloads).
Core engineering & delivery: Expert in Golang and Python (concurrency, memory, performance tuning) and high-throughput asynchronous systems (messaging queues/ Pub-Sub); Responsible AI/ data governance/ compliance experience is a plus; strong mentoring, stakeholder management, and end-to-end delivery capability.
