R&D Efficiency Architect

Responsibilities:

Deeply identify inefficiencies across all stages of the R&D process, including but not limited to project collaboration, requirements management, development management, quality management, and operations management. Propose innovative improvement measures, drive their implementation, and enhance overall R&D efficiency.

Abstract requirements based on user pain points from different roles (e.g., product managers, software engineers, QA engineers, operations personnel), complete the overall design, development, and optimization of the R&D efficiency platform, and build a low-code-style R&D efficiency pipeline.

Perform comprehensive analysis of R&D efficiency–related data to uncover process bottlenecks and optimization opportunities, address real-world challenges in implementing R&D efficiency within the company, and provide technical support, training, and best-practice guidance.

Design and optimize the efficiency platform architecture to ensure system scalability, high availability, stability, and security, meeting the diverse needs of R&D teams.

Drive the implementation of automation tools and processes to improve team delivery efficiency, quality, and collaboration. Collaborate closely with R&D, product, and operations teams to develop technical strategies and resolve complex issues.

Requirements:

Experience and Leadership:

At least five years of DevOps implementation experience and experience leading R&D teams. Proficient in project management knowledge and tools (e.g., Meegle, Jira, Confluence) as well as software design and development.

Familiar with Agile and Lean methodologies, and able to effectively drive team collaboration and process optimization.

Technical Depth:

Deep understanding of general system architecture, configuration, and management, including but not limited to Infrastructure as Code (IaC) tools (e.g., Terraform, Pulumi), continuous integration (CI), and continuous deployment (CD) tools (e.g., Jenkins, GitLab CI). Familiar with AWS, cloud-native technologies (e.g., Kubernetes, Docker), and site reliability engineering (SRE), with the ability to flexibly apply cloud services and containerization technologies.

Solid programming skills, proficient in at least one backend development language (e.g., Java, Go, or Python). Familiarity with frontend technologies (e.g., React, Vue, TypeScript) is a plus.

System Design and Collaboration:

Strong system design capabilities, familiar with actual R&D processes, and able to design high-performance, scalable system architectures.

Extensive experience interfacing with product management, project management, R&D, QA, and operations to ensure seamless integration between the platform and business requirements.

Data Analysis and Insights:

Strong data analysis skills, adept at deriving insights from R&D efficiency data and driving solutions. Able to optimize processes using BI tools (e.g., Tableau, Power BI) or custom data analysis systems.

Basic big data processing capabilities, able to perform simple data processing and analysis using NoSQL, OLAP, Flink/Spark, or other big data tools (expert-level proficiency not required, but understanding of big data applications in R&D efficiency analysis is necessary).

Team Collaboration:

Excellent communication skills, able to clearly convey technical concepts and coordinate cross-departmental collaboration effectively.

Outstanding team management and coordination abilities, able to lead teams to complete complex projects and drive technology implementation.

Detail-oriented, proactive, and able to perform efficiently under pressure in high-stress environments.

Bonus Points:

Familiarity with the latest trends in R&D efficiency (e.g., DevOps best practices, efficiency metrics such as DORA metrics) is preferred.

Experience in training and knowledge sharing, able to provide technical guidance and best practices to the team.

Responsibilities:

Deeply identify inefficiencies across all stages of the R&D process, including but not limited to project collaboration, requirements management, development management, quality management, and operations management. Propose innovative improvement measures, drive their implementation, and enhance overall R&D efficiency.

Abstract requirements based on user pain points from different roles (e.g., product managers, software engineers, QA engineers, operations personnel), complete the overall design, development, and optimization of the R&D efficiency platform, and build a low-code-style R&D efficiency pipeline.

Perform comprehensive analysis of R&D efficiency–related data to uncover process bottlenecks and optimization opportunities, address real-world challenges in implementing R&D efficiency within the company, and provide technical support, training, and best-practice guidance.

Design and optimize the efficiency platform architecture to ensure system scalability, high availability, stability, and security, meeting the diverse needs of R&D teams.

Drive the implementation of automation tools and processes to improve team delivery efficiency, quality, and collaboration. Collaborate closely with R&D, product, and operations teams to develop technical strategies and resolve complex issues.

Requirements:

Experience and Leadership:

At least five years of DevOps implementation experience and experience leading R&D teams. Proficient in project management knowledge and tools (e.g., Meegle, Jira, Confluence) as well as software design and development.

Familiar with Agile and Lean methodologies, and able to effectively drive team collaboration and process optimization.

Technical Depth:

Deep understanding of general system architecture, configuration, and management, including but not limited to Infrastructure as Code (IaC) tools (e.g., Terraform, Pulumi), continuous integration (CI), and continuous deployment (CD) tools (e.g., Jenkins, GitLab CI). Familiar with AWS, cloud-native technologies (e.g., Kubernetes, Docker), and site reliability engineering (SRE), with the ability to flexibly apply cloud services and containerization technologies.

Solid programming skills, proficient in at least one backend development language (e.g., Java, Go, or Python). Familiarity with frontend technologies (e.g., React, Vue, TypeScript) is a plus.

System Design and Collaboration:

Strong system design capabilities, familiar with actual R&D processes, and able to design high-performance, scalable system architectures.

Extensive experience interfacing with product management, project management, R&D, QA, and operations to ensure seamless integration between the platform and business requirements.

Data Analysis and Insights:

Strong data analysis skills, adept at deriving insights from R&D efficiency data and driving solutions. Able to optimize processes using BI tools (e.g., Tableau, Power BI) or custom data analysis systems.

Basic big data processing capabilities, able to perform simple data processing and analysis using NoSQL, OLAP, Flink/Spark, or other big data tools (expert-level proficiency not required, but understanding of big data applications in R&D efficiency analysis is necessary).

Team Collaboration:

Excellent communication skills, able to clearly convey technical concepts and coordinate cross-departmental collaboration effectively.

Outstanding team management and coordination abilities, able to lead teams to complete complex projects and drive technology implementation.

Detail-oriented, proactive, and able to perform efficiently under pressure in high-stress environments.

Bonus Points:

Familiarity with the latest trends in R&D efficiency (e.g., DevOps best practices, efficiency metrics such as DORA metrics) is preferred.

Experience in training and knowledge sharing, able to