Solution Architect_3942

Brief description of the position:

This position requires a technical background. You will be responsible for the design and development of backend services for the vehicle service platform, ensuring high availability, high reliability, and high security of the services while supporting core business scenarios. Additionally, you will be responsible for the design and development of AI-related services, such as core AI functional modules (e.g., Large Language Model applications, intelligent dialogue engines, recommendation algorithm services) and the full lifecycle management of AI models. You will also lead the design and implementation of AI capability integration solutions across multiple systems.

Key Tasks:

Participate in the planning and optimization of the vehicle service platform architecture, splitting and designing service modules based on microservice architecture concepts.

Develop and optimize distributed systems, resolving core issues such as service registration and discovery, load balancing, circuit breaking, and degradation.

Lead or participate in the implementation of containerized deployment solutions, completing service deployment, orchestration, monitoring, and operations based on Kubernetes (K8S).

Responsible for the practical application and optimization of cloud services, reasonably selecting cloud products such as ECS, RDS, MQ, and OSS to support business requirements.

Participate in solving technical challenges, keeping up with new technologies and trends in backend development, and applying suitable technical solutions to business requirements.

Cooperate with product, testing, and operations teams to complete tasks such as requirement alignment and troubleshooting.

Responsible for the design and development of AI-related services, including core AI functional modules (e.g., Large Language Model applications, intelligent dialogue engines, recommendation algorithm services) and the full lifecycle management of AI models.

Lead the design and implementation of AI capability integration solutions across multiple systems, integrating with mainstream large model providers and third-party AI systems.

Build a core data monitoring system for AI services (covering response latency, token consumption, user satisfaction, etc.), identifying issues through data analysis and driving continuous optimization.

Compile and accumulate documentation such as AI product white papers and technical integration manuals to support the team.

Qualification and Skills:

Education: A bachelor’s degree or higher in Information Technology, Computer Science, Electrical Engineering, Automotive Engineering, Artificial Intelligence, or a related field.

Experience: Over 3 years of relevant work experience in microservices and cloud services, with the ability to conduct architecture design and performance optimization, and development experience in projects related to core services. Additionally, possess over 3 years of practical work experience in AI products or related fields, and be familiar with the product design logic of at least one core AI scenario (such as Natural Language Processing, Computer Vision, or Intelligent Recommendation).

Knowledge, Skills, and Others:

Proficient in at least one backend development language (e.g., Java).

In-depth understanding of microservice architecture concepts, with experience in microservice splitting, design, and development. Proficient in at least one microservice development framework (e.g., Spring Cloud, Dubbo, Go Micro, etc.).

Proficient in containerization technology, familiar with the construction, packaging, and management of Docker containers. Possess solid Kubernetes (K8S) experience, and be proficient in K8S core components (Pod, Service, Deployment, ConfigMap, etc.) and operations.

Possess solid practical experience in AI projects, with a deep understanding of fundamental AI concepts (such as Machine Learning, Deep Learning, Large Language Models, Transformer architecture, Prompt Engineering, etc.).

Familiar with mainstream AI API specifications, vector database principles, and RAG (Retrieval-Augmented Generation) architecture design, capable of resolving various technical issues in AI application development.

Familiar with identity authentication protocols such as SSO (Single Sign-On) and OAuth2.0/OIDC.

Familiar with middleware such as MySQL, Redis, RabbitMQ/Kafka, possessing experience in cache strategy development and ensuring message reliability.