Job Responsibilities
1. Core System Architecture Design & Optimization
(1) Complex System Architecture Design
a. Lead architecture design and iteration of CIC Smart Community Platform core modules, supporting high-concurrency/high-availability scenarios for millions of DAU, including disaster recovery solutions and security frameworks (e.g., cross-border data encryption, payment risk control).
b. Drive tech stack upgrades: Optimize existing .NET systems (ASP.NET Core + Entity Framework), lead Golang adoption in microservice gateways, real-time data processing (e.g., IoT device message streams), and design phased migration strategies.
2. AI Engineering & Business Integration
(1) AI Model Service Deployment
a. Design high-performance AI service architectures (NLP/CV domains) for smart property prediction and cross-border service recommendation, deploy models via TensorFlow Serving/TorchServe, optimize GPU resource allocation, and build monitoring systems.
b. Build end-to-end ML pipelines integrating data cleaning, feature engineering, model training/inference, and improve AI service throughput (e.g., 30% QPS increase) and resource efficiency (e.g., 20% GPU cost reduction).
3. Technical Leadership & Engineering Efficiency
(1) Team Enablement
a. Establish coding standards, automate testing (≥80% unit/integration test coverage), and CI/CD pipelines (GitLab CI + ArgoCD). Enhance delivery quality via code reviews and toolchain optimization.
b. Resolve technical challenges: Distributed transactions (Seata/Saga), multi-language payment gateway integration (Alipay Global, Stripe), cross-border data synchronization (eventual consistency), and build reusable solution libraries.
4. Business-Driven Innovation
(1) Vertical Domain Expertise
a. Design high-availability architectures for property management and cross-border services (e.g., O2O resource scheduling algorithms, distributed inventory systems for reward stores), optimizing metrics like ≤50ms order processing latency.
b. Explore cutting-edge tech: Implement blockchain-based decentralized reward settlement, design AI-driven user growth models (LTV prediction, personalized recommendations), and lead tech-driven product innovation.
Requirements
1. Mandatory Qualifications
(1) Education & Experience
a. Bachelor’s degree or above in Computer Science; 10+ years of backend development experience, including:5+ years in .NET: Led ASP.NET Core microservice projects, proficient in EF Core performance tuning.3+ years in Golang: Experience with high-concurrency/distributed systems (e.g., Etcd, NSQ).2+ architecture designs for systems with millions of DAU, covering full lifecycle (requirements analysis, tech selection, deployment).
b. 1+ end-to-end AI project implementation (from design to production).
2. Technical Competencies
(1) Core Languages & Frameworks
a. .NET Expert: Master ASP.NET Core microservices (gRPC/Consul), EF Core advanced features (lazy loading/query optimization), Docker/K8s deployment.
OR Java Expert: Proficient in Java stack (JVM, Spring ecosystem, MyBatis, Netty), microservices, and middleware (Nacos, Seata).
b. Golang Advanced: Deep understanding of Goroutine scheduling, Channel mechanics, Gin/Echo framework optimization, and distributed middleware (Etcd service discovery).
(2) AI Engineering
a. Skilled in PyTorch/TensorFlow model deployment (ONNX optimization, Triton inference), GPU resource monitoring (Prometheus + Grafana), and auto-scaling strategies.
3. Bonus Skills
(1) Familiarity with Python data analysis (Pandas/Spark) or scripting for AI data processing/operations.
4. Soft Skills
(1) Language & Collaboration
a. Proficient in reading technical documentation in English; fluency in Cantonese preferred (collaboration with Hong Kong/GBA teams).
(2) Technical Leadership
a. Strong decision-making and risk management skills, balancing business agility with tech debt reduction (e.g., debt repayment plans).
b. Passion for emerging tech: Prior experience with Serverless architecture or LLM applications is a plus.
5. Key Notes:
(1) Precision: Technical jargon (e.g., "eventual consistency," "Goroutine scheduling") is retained for clarity.
(2) Localization: Emphasizes cross-border (e.g., Alipay/Stripe integration) and regional (Hong Kong/GBA) requirements.
Metrics-Driven: Highlights quantifiable outcomes (QPS, GPU cost reduction) to align with business goals.