
1. Shipment Tracking & Communication
2. Issue Resolution & Problem Solving
3. Documentation & Compliance
4. Customer Service Excellence
5. Flight Operations Support
1. Sales Development
2. Sales Data
3. Coordination
4. Relationship Management
5. 5.Product Support
China National Aviation Holding Corporation Limited
(Air China Limited)
2026 International Talent Recruitment:
Artificial Intelligence Expert
Work Location
Shenzhen Airlines Company Limited, Shenzhen
Recruiting Organization Overview
China National Aviation Holding Corporation Limited ("CNAH") was established on October 11, 2002. It is a major state-owned air transportation group and the only air transportation enterprise in China flying the national flag. CNAH has seven principal second-tier companies, including Air China Limited, China National Aviation Corporation (Group) Limited, Air China Cargo Co., Ltd., Zhongyi Aviation Investment Co., Ltd., China National Aviation Construction and Development Company, China National Aviation Capital Holding Co., Ltd., and China National Aviation Media Co., Ltd. Its businesses span two core sectors—air passenger transportation, and air cargo and logistics—as well as closely related sectors including aircraft maintenance, airline catering, cargo terminals, ground services, airport services and aviation media, and extended service sectors including financial services, aviation tourism, engineering construction and information networks. CNAH has more than 100,000 employees. CNAH actively promotes professionalized management of media, leasing and comprehensive support services, as well as integrated management of centralized procurement, airline catering, information technology and human resources services. It advances group-wide industrial collaboration and coordinated planning, and has basically formed an integrated development structure encompassing diversified aviation-related businesses including passenger transportation, cargo transportation, maintenance, catering, media, investment and comprehensive support. As of June 30, 2026, CNAH (including its controlled companies) operated 1,000 aircraft. Through cooperation with Star Alliance member airlines and other carriers, CNAH has extended its passenger and cargo services to more than 1,100 destinations in over 190 countries and regions.
Shenzhen Airlines Company Limited ("Shenzhen Airlines"), a member company of CNAH, is headquartered in Shenzhen. It was established in November 1992 and operated its inaugural flight on September 17, 1993. As of June 2026, Shenzhen Airlines had 8 branches, 5 bases and 3 major wholly owned subsidiaries, with a fleet of more than 200 aircraft. Its route network basically covers provincial capitals and key cities in mainland China, Hong Kong, Macao and Taiwan, as well as the United Kingdom, Spain, Qatar, Australia, Japan, South Korea and Southeast Asian countries, and it transports nearly 40 million passengers annually. Shenzhen Airlines takes "Creating a Better Life" as its mission and upholds the core values of "safety first, customer orientation, seeking excellence, and valuing value creators." Looking ahead, Shenzhen Airlines will seize the strategic opportunities arising from the development of the Guangdong-Hong Kong-Macao Greater Bay Area and Shenzhen's development as a pilot demonstration zone of socialism with Chinese characteristics, uphold the bottom line of flight safety, steadily expand its fleet, continuously improve service quality, and strive to become "an Airline of Widespread Popularity and All-round Excellence," better serving people's aspirations for a better life.
Position Overview
I. Key Responsibilities:
1. Lead the Company's AI technology strategy planning and key technology selection decisions, and formulate the AI development roadmap and implementation path;
2. Lead the design of core AI technology architecture and major technical breakthroughs, ensuring that technical solutions are advanced and implementable;
3. Drive deep integration of AI with core business scenarios and lead the full process from technical validation to scaled implementation;
4. Establish the Company's AI technology standards system, R&D specifications and e
ngineering infrastructure;
5. Lead the Company's algorithm team in overcoming key technical challenges, develop core technical talent, and enhance the team's overall technical judgment and engineering capabilities.
II. Number of Openings: 1
III. Qualifications & Requirements
• Education: Must hold a Ph.D. degree. Graduates of institutions in mainland China must provide their graduation certificate and degree certificate. Graduates of institutions outside mainland China must provide an Overseas Credentials Evaluation Report issued by the Chinese Service Center for Scholarly Exchange (CSCSE) under the Ministry of Education.
• Preferred Academic Background: A degree in Computer Science and Technology, Big Data, Artificial Intelligence, or a related field is preferred.
• Professional Expertise:
(1) AI Strategy Planning & Coordination: Ability to formulate enterprise-level medium- and long-term AI strategies and implementation paths; accurately identify the intersection of technology trends and business needs; lead key technology selection decisions; and coordinate cross-departmental resources to drive strategy implementation.
(2) Technology Standards System Development: Ability to lead the establishment of an enterprise-level AI technology standards system, algorithm R&D specifications and engineering infrastructure; build standardized lifecycle management across data governance, model evaluation, safety and compliance, and operations processes; and provide institutional and technical support for scaled AI applications.
(3) Core Technology R&D & Breakthroughs: Ability to design core AI architectures and independently develop frontier technologies; lead technical breakthroughs in areas such as large language models and intelligent decision algorithms; solve complex technical challenges including high-concurrency inference, controllable model generation and domain-knowledge integration; and ensure that technical solutions are advanced, reliable and implementable.
(4) End-to-End AI Application & Value Realization: Ability to deeply integrate AI with core business scenarios; lead closed-loop management from demand analysis, technical validation and pilot deployment to scaled application; and ensure that AI applications deliver tangible business value, improve operational efficiency and enhance service quality.
• Research Capabilities:
(1) Frontier Technology Insight: Systematic technical understanding of frontier areas such as large language models, multimodal learning and generative AI; ability to clearly explain the evolution and selection rationale of key technology routes; and ability to accurately identify technology trends and industry application inflection points.
(2) Technical Decision-Making Judgment: A verifiable track record of judgment in key technology-selection or architecture-design decisions; ability to rationally balance business-scenario requirements and technology maturity; and ability to make technical decisions that are both forward-looking and pragmatic.
(3) End-to-End R&D Practice: Deep involvement in the complete process of AI systems from R&D through production launch, with hands-on experience in large-scale system design and engineering delivery.
(4) Academic-to-Engineering Translation: Ability to translate frontier academic outcomes into implementable engineering solutions; successful experience in industry-academia-research commercialization or technology transfer; and ability to build effective bridges between academic frontiers and industrial practicality.
(5) Industry Scenario Understanding & Cross-Domain Integration: International perspective and industry understanding of AI applications in aviation, transportation or industrial sectors; ability to deeply integrate general-purpose AI with vertical-domain expertise; and ability to identify high-value application scenarios and drive technical adaptation.
• Work Experience Requirements:
1. At least 5 years of work experience. After obtaining a Ph.D., candidates must have held a formal position for at least 36 consecutive months at a renowned overseas university, research institution, enterprise, or its R&D institution. For candidates who obtained their Ph.D. overseas, the work-experience duration requirement may be appropriately relaxed (this relaxation does not apply to overseas Ph.D. degrees obtained through Sino-foreign joint training programs). Candidates must currently be studying or working overseas, or have returned to China for work after January 1, 2026. In addition, candidates must be available for at least one full term of full-time employment (3 years).
2. Achievement Requirements:
(1) Led the end-to-end implementation of an AI product or system—from requirements definition and technology selection through production launch and operations—and achieved quantifiable business results (consumer-facing: tens of millions of users; business-facing: coverage of core business processes or at least one million endpoints);
(2) Served as a core decision-maker in at least one major project where a key technology selection was validated as the correct decision, with the ability to review and explain the decision logic and outcomes;
(3) Held granted invention patents as the first or principal inventor, or led an influential open-source technology project in the industry;
(4) Had complete experience building an AI team or technology system from scratch, with the team remaining capable of independent operation and sustained delivery after the candidate's departure;
(5) Led technical breakthrough projects whose outcomes generated substantive industry impact, such as adoption by peers, industry recognition, or significant cost reduction and efficiency improvement.
• Capabilities & Attributes:
1. Ability to pioneer new research areas or solve critical technical problems in professional practice.
2. Strategic vision and foresight, capable of tracking cutting-edge developments in the field, with acute insight and the ability to integrate advanced technologies.
3. Strong systematic thinking and complex-management thinking, resilience under pressure, sound decision-making skills, and excellent problem-diagnosis capabilities.
Compensation & Benefits
CNAH will offer a market-competitive compensation and benefits package. Specific compensation will be determined based on the applicant's interview performance and subsequent compensation discussions.
Application Method & Deadline
I. Application Method
Applications are accepted online only. Please visit the CNAH recruitment website (http://zhaopin.airchina.com.cn/), register, and apply as instructed.
II. Application Deadline: 5:00 p.m. on October 23, 2026 (Beijing Time).
III. Contact Information
Mr. Sun
Email: capx2020@163.com
Recruitment Process
The recruitment process will generally follow these stages: announcement posting, qualification review, interview and comprehensive evaluation, background check, and final selection. Specific implementation times, locations and other arrangements for each stage will be communicated by email, SMS or telephone. Applicants should monitor these communications and remain reachable.
Important Notes
• Before applying, applicants should first review the relevant information and requirements for this recruitment.
• Applicants are responsible for the authenticity of the application materials they submit. If any information is found to be inconsistent with the facts, CNAH reserves the right to revoke the applicant's eligibility for assessment and employment, and the applicant shall bear any consequences arising therefrom.
China National Aviation Holding Corporation Limited
(Air China Limited)
2026 International Talent Recruitment:
Artificial Intelligence & Predictive Maintenance Expert
Work Location
Shenzhen Airlines Company Limited, Shenzhen
Recruiting Organization Overview
China National Aviation Holding Corporation Limited ("CNAH") was established on October 11, 2002. It is a major state-owned air transportation group and the only air transportation enterprise in China flying the national flag. CNAH has seven principal second-tier companies, including Air China Limited, China National Aviation Corporation (Group) Limited, Air China Cargo Co., Ltd., Zhongyi Aviation Investment Co., Ltd., China National Aviation Construction and Development Company, China National Aviation Capital Holding Co., Ltd., and China National Aviation Media Co., Ltd. Its businesses span two core sectors—air passenger transportation, and air cargo and logistics—as well as closely related sectors including aircraft maintenance, airline catering, cargo terminals, ground services, airport services and aviation media, and extended service sectors including financial services, aviation tourism, engineering construction and information networks. CNAH has more than 100,000 employees. CNAH actively promotes professionalized management of media, leasing and comprehensive support services, as well as integrated management of centralized procurement, airline catering, information technology and human resources services. It advances group-wide industrial collaboration and coordinated planning, and has basically formed an integrated development structure encompassing diversified aviation-related businesses including passenger transportation, cargo transportation, maintenance, catering, media, investment and comprehensive support. As of June 30, 2026, CNAH (including its controlled companies) operated 1,000 aircraft. Through cooperation with Star Alliance member airlines and other carriers, CNAH has extended its passenger and cargo services to more than 1,100 destinations in over 190 countries and regions.
Shenzhen Airlines Company Limited ("Shenzhen Airlines"), a member company of CNAH, is headquartered in Shenzhen. It was established in November 1992 and operated its inaugural flight on September 17, 1993. As of June 2026, Shenzhen Airlines had 8 branches, 5 bases and 3 major wholly owned subsidiaries, with a fleet of more than 200 aircraft. Its route network basically covers provincial capitals and key cities in mainland China, Hong Kong, Macao and Taiwan, as well as the United Kingdom, Spain, Qatar, Australia, Japan, South Korea and Southeast Asian countries, and it transports nearly 40 million passengers annually. Shenzhen Airlines takes "Creating a Better Life" as its mission and upholds the core values of "safety first, customer orientation, seeking excellence, and valuing value creators." Looking ahead, Shenzhen Airlines will seize the strategic opportunities arising from the development of the Guangdong-Hong Kong-Macao Greater Bay Area and Shenzhen's development as a pilot demonstration zone of socialism with Chinese characteristics, uphold the bottom line of flight safety, steadily expand its fleet, continuously improve service quality, and strive to become "an Airline of Widespread Popularity and All-round Excellence," better serving people's aspirations for a better life.
Position Overview
I. Key Responsibilities:
1. Lead the top-level design and technology roadmap planning for the Company's predictive maintenance system, and drive the deep application of AI technology in aircraft maintenance;
2. Lead the development of an aircraft full-lifecycle Prognostics and Health Management (PHM) system to enable data-driven fault prediction and intelligent decision-making;
3. Lead the team in developing predictive-maintenance models and optimizing algorithms for key components such as engines, APUs and landing gear;
4. Coordinate maintenance data governance and knowledge-graph development, breaking down data silos across flight data, maintenance records and supply-chain data;
5. Track international frontier technologies in intelligent aviation maintenance and establish a technical cooperation ecosystem with OEMs and research institutions;
6. Develop an AI+Maintenance interdisciplinary talent pipeline and enhance the organization's digital capabilities.
II. Number of Openings: 1
III. Qualifications & Requirements
• Education: Must hold a Ph.D. degree. Graduates of institutions in mainland China must provide their graduation certificate and degree certificate. Graduates of institutions outside mainland China must provide an Overseas Credentials Evaluation Report issued by the Chinese Service Center for Scholarly Exchange (CSCSE) under the Ministry of Education.
• Preferred Academic Background: A degree in Computer Science and Technology, Artificial Intelligence, Data Science, Aerospace Engineering, Mechanical Engineering (predictive maintenance), or a related field is preferred.
• Professional Expertise:
(1) Expertise in machine learning, deep learning, time-series analysis and related algorithms, with R&D experience in aviation PHM systems;
(2) Proficiency in data-science tools such as Python and R, and familiarity with deep-learning frameworks such as TensorFlow and PyTorch;
(3) Professional knowledge of aviation maintenance engineering, with familiarity with failure modes and failure mechanisms of key systems such as engine systems and airframe structures;
(4) Capability in big-data platform architecture design, with familiarity with cloud-computing and edge-computing applications in aviation maintenance scenarios;
(5) Excellent interdisciplinary communication and project-management skills, with the ability to coordinate collaboration between technical and business teams;
(6) Good English communication skills, with the ability to read aviation technical literature and conduct international technical exchanges.
• Research Capabilities:
(1) Publication of high-level papers or grants of core patents related to predictive maintenance, fault diagnosis or health management in aviation;
(2) Experience leading or participating in national-level or provincial/ministerial-level research projects on aviation intelligentization is preferred;
(3) Experience in technical cooperation projects with the International Air Transport Association (IATA), engine manufacturers (OEMs), or internationally renowned airlines is preferred;
(4) Ability to translate frontier AI technologies into engineering applications, with successful implementation cases in aviation maintenance;
(5) Membership in international academic organizations such as IEEE or AIAA, or experience as a journal reviewer, is preferred.
• Work Experience Requirements:
1. After obtaining a Ph.D., candidates must have held a formal position for at least 36 consecutive months at a renowned overseas university, research institution, enterprise, or its R&D institution. For candidates who obtained their Ph.D. overseas, the work-experience duration requirement may be appropriately relaxed (this relaxation does not apply to overseas Ph.D. degrees obtained through Sino-foreign joint training programs). Candidates must currently be studying or working overseas, or have returned to China for work after January 1, 2026. In addition, candidates must be available for at least one full term of full-time employment (3 years).
2. Achievement Requirements (must meet at least one of the following):
(1) Led intelligentization projects at the ten-million level or above in the aviation sector, or led PHM system development, and delivered quantifiable business value;
(2) Holds more than 3 core technology patents, or has influential achievements in the field of AI applications for aviation maintenance;
(3) Led a team in completing major technical breakthroughs that significantly reduced maintenance costs or significantly improved safety performance;
(4) Candidates who have received provincial/ministerial-level or higher science and technology awards, or authoritative industry awards, are preferred.
• Capabilities & Attributes:
1. Ability to pioneer new research areas or solve critical technical problems in professional practice.
2. Strategic vision and foresight, capable of tracking cutting-edge developments in the field, with acute insight and the ability to integrate advanced technologies.
3. Strong systematic thinking and complex-management thinking, resilience under pressure, sound decision-making skills, and excellent problem-diagnosis capabilities.
Compensation & Benefits
CNAH will offer a market-competitive compensation and benefits package. Specific compensation will be determined based on the applicant's interview performance and subsequent compensation discussions.
Application Method & Deadline
I. Application Method
Applications are accepted online only. Please visit the CNAH recruitment website (http://zhaopin.airchina.com.cn/), register, and apply as instructed.
II. Application Deadline: 5:00 p.m. on October 23, 2026 (Beijing Time).
III. Contact Information
Mr. Sun
Email: capx2020@163.com
Recruitment Process
The recruitment process will generally follow these stages: announcement posting, qualification review, interview and comprehensive evaluation, background check, and final selection. Specific implementation times, locations and other arrangements for each stage will be communicated by email, SMS or telephone. Applicants should monitor these communications and remain reachable.
Important Notes
• Before applying, applicants should first review the relevant information and requirements for this recruitment.
• Applicants are responsible for the authenticity of the application materials they submit. If any information is found to be inconsistent with the facts, CNAH reserves the right to revoke the applicant's eligibility for assessment and employment, and the applicant shall bear any consequences arising therefrom.
China National Aviation Holding Corporation Limited
(Air China Limited)
2026 International Talent Recruitment:
Senior Researcher – Aviation Digitalization & AI
Work Location
Chengdu Falcon Aircraft Engineering Service Co., Ltd., Chengdu
Recruiting Organization Overview
China National Aviation Holding Corporation Limited ("CNAH") was established on October 11, 2002. It is a major state-owned air transportation group and the only air transportation enterprise in China flying the national flag. CNAH has seven principal second-tier companies, including Air China Limited ("Air China"), China National Aviation Corporation (Group) Limited, Air China Cargo Co., Ltd., Zhongyi Aviation Investment Co., Ltd., China National Aviation Construction and Development Company, China National Aviation Capital Holding Co., Ltd., and China National Aviation Media Co., Ltd. Its businesses span two core sectors—air passenger transportation, and air cargo and logistics—as well as closely related sectors including aircraft maintenance, airline catering, cargo terminals, ground services, airport services and aviation media, and extended service sectors including financial services, aviation tourism, engineering construction and information networks. CNAH has more than 100,000 employees. CNAH actively promotes professionalized management of media, leasing and comprehensive support services, as well as integrated management of centralized procurement, airline catering, information technology and human resources services. It advances group-wide industrial collaboration and coordinated planning, and has basically formed an integrated development structure encompassing diversified aviation-related businesses including passenger transportation, cargo transportation, maintenance, catering, media, investment and comprehensive support. As of June 30, 2026, CNAH (including its controlled companies) operated 1,000 aircraft. Through cooperation with Star Alliance member airlines and other carriers, CNAH has extended its passenger and cargo services to more than 1,100 destinations in over 190 countries and regions.
Chengdu Falcon Aircraft Engineering Service Co., Ltd. (hereinafter referred to as the "Company") was established in July 2001 and is a Sino-foreign joint venture controlled by Air China. Headquartered in Chengdu, the Company has nine operating and management support departments: Component Maintenance Department, Aircraft Modification Department, Research and Development Department, Quality Department, Marketing Department, Finance Department, Production Support Department, Human Resources and Party-Mass Affairs Department, and General Management Department. It also has a wholly owned subsidiary, Chengdu Juxin Aviation Equipment Co., Ltd., and the subsidiary's Chongqing Branch. The Company has nearly 440 employees. In 2020, the Company was selected as a national "Science and Technology Reform Demonstration Enterprise." It is also a National High-tech Enterprise, a Sichuan Provincial "Specialized, Sophisticated, Unique and Innovative" SME, a Sichuan Provincial Service-oriented Manufacturing Demonstration Enterprise, and a Sichuan Provincial Enterprise Technology Center.
After more than two decades of dedicated development, the Company has obtained CAAC 145, FAA 145, EASA 145, JMM, DMDOR, PC, PMA and CTSOA certifications and approvals. In aircraft modification, the Company is a full-chain modification solution provider in its specialized field; in component maintenance, it serves as a "Center of Excellence" for specific component product families. Guided by its vision of "leading the development of China's aircraft modification industry and building a well-known aircraft component maintenance brand in China and overseas," the Company is committed to achieving long-term sustainable development.
Position Overview
I. Key Responsibilities:
1. Lead the implementation of AI technologies in scenarios including aircraft component and accessory failure prediction and maintenance management, digital job cards, and image-based visual troubleshooting;
2. Lead the application of digital-twin technology in aircraft component and accessory maintenance and aircraft modification design;
3. Lead the application of frontier technologies such as intelligent manufacturing, the Industrial Internet of Things, and big-data analytics in aviation manufacturing;
4. Build and lead the Company's digitalization and intelligentization R&D team, and establish an AI talent development system.
II. Number of Openings: 1
III. Qualifications & Requirements
• Education: Must hold a Ph.D. degree. Graduates of institutions in mainland China must provide their graduation certificate and degree certificate. Graduates of institutions outside mainland China must provide an Overseas Credentials Evaluation Report issued by the Chinese Service Center for Scholarly Exchange (CSCSE) under the Ministry of Education.
• Preferred Academic Background: A degree in Artificial Intelligence, Computer Science and Technology, Software Engineering, or a related field is preferred.
• Professional Expertise: Familiarity with machine learning, deep learning and related algorithms; ability and relevant R&D experience in deploying algorithms in real business scenarios; proficiency in Python and familiarity with mainstream deep-learning frameworks such as TensorFlow; strong cross-departmental coordination and team-management capabilities; and ability to drive organizational change and cultural transformation.
• Research Capabilities: R&D experience in large language models, computer vision, natural language processing or related fields is preferred; work and project experience at leading technology companies or research institutions is preferred; relevant technology patents and publication of high-level academic papers are preferred.
• Work Experience Requirements:
1. After obtaining a Ph.D., candidates must have held a formal position for at least 36 consecutive months at a renowned overseas university, research institution, enterprise, or its R&D institution. For candidates who obtained their Ph.D. overseas, the work-experience duration requirement may be appropriately relaxed (this relaxation does not apply to overseas Ph.D. degrees obtained through Sino-foreign joint training programs). Candidates must currently be studying or working overseas, or have returned to China for work after January 1, 2026. In addition, candidates must be available for at least one full term of full-time employment (3 years).
2. Achievement Requirements: successful cases of applying AI technology in aviation maintenance, manufacturing or modification business scenarios; core technology patents or influential technical achievements in the industry; and experience leading a team to complete major technical breakthrough projects.
• Capabilities & Attributes:
1. Ability to pioneer new research areas or solve critical technical problems in professional practice.
2. Strategic vision and foresight, capable of tracking cutting-edge developments in the field, with acute insight and the ability to integrate advanced technologies.
3. Strong systematic thinking and complex-management thinking, resilience under pressure, sound decision-making skills, and excellent problem-diagnosis capabilities.
Compensation & Benefits
CNAH will offer a market-competitive compensation and benefits package. Specific compensation will be determined based on the applicant's interview performance and subsequent compensation discussions.
Application Method & Deadline
I. Application Method
Applications are accepted online only. Please visit the CNAH recruitment website (http://zhaopin.airchina.com.cn/), register, and apply as instructed.
II. Application Deadline: 5:00 p.m. on October 23, 2026 (Beijing Time).
III. Contact Information
Mr. Sun
Email: capx2020@163.com
Recruitment Process
The recruitment process will generally follow these stages: announcement posting, qualification review, interview and comprehensive evaluation, background check, and final selection. Specific implementation times, locations and other arrangements for each stage will be communicated by email, SMS or telephone. Applicants should monitor these communications and remain reachable.
Important Notes
• Before applying, applicants should first review the relevant information and requirements for this recruitment.
• Applicants are responsible for the authenticity of the application materials they submit. If any information is found to be inconsistent with the facts, CNAH reserves the right to revoke the applicant's eligibility for assessment and employment, and the applicant shall bear any consequences arising therefrom.