阿里云智能-计算平台解决方案-大数据AI产品解决方案国际业务

1. Overseas Big Data & AI Market Insight and Competitive Analysis

• Identify market opportunities, assess market capacity, and analyze the competitive landscape for Big Data and AI products in overseas markets.

• Analyze core metrics, market strategies, and pricing models of international competitors.

• Rapidly capture emerging market trends and customer pain points to uncover business opportunities, accelerate solution deployment, and establish a leading competitive edge.

2. International Business Opportunity Assessment and Deep Technical Engagement for Big Data & AI Products

• Represent the product line in designing international business strategies and evaluating commercial opportunities for Big Data and AI products.

• For complex project requirements, collaborate with sales teams to conduct deep technical exchanges with customers. Leverage insights into industry trends and technological shifts to guide key decision-makers in specific technical scenarios, thereby facilitating opportunity conversion.

• Conduct in-depth technical discussions and present product solutions to international clients and English-speaking stakeholders.

3. Solution Design and Technical Support for Big Data & AI Products

• For complex projects, thoroughly understand customer business needs, functional/non-functional requirements, performance, and availability standards. Based on specific customer scenarios, deliver technically competitive, feasible, and cost-effective product combination solutions. Provide technical support during product selection, Proof of Concept (PoC), and quotation configuration.

• Extract key technical indicators based on customer business scenarios to formulate leading control criteria, validating them through PoCs, win-back initiatives, and other business activities.

• Drive cross-team collaboration to optimize solutions for complex projects, enhancing competitiveness across multiple dimensions including cost, performance, and stability.

• Explore solutions and scenarios for innovative products to accelerate market coverage and ensure sustained product innovation vitality.

• Provide critical post-sales technical Q&A for key accounts, leveraging technology to drive business growth.

4. Product Design and Optimization Support for Big Data & AI Products

• Leverage deep understanding of industries and scenarios to participate in the design of major product features, pricing strategies, and user experiences, ensuring the product maintains leadership within specific sectors and use cases.

• Identify and precisely distill common customer needs and pain points to feed back into product design, driving product improvements, multi-product integration, and the incubation of new products and features.

5. Best Practice Accumulation and Enablement

• Consolidate best practices for niche scenarios; selectively output Infrastructure as Code (IaC) scripts. Summarize benchmark success stories from project implementations to extract common modules and standardize capabilities, accelerating the scaled replication of product solutions.

• Highlight product features and performance parameters, designing targeted test cases to amplify product and technical influence. Build solution competitiveness grounded in robust test cases and testing methodologies.

• Contribute to the development of Go-to-Market (GTM) materials for Big Data and AI products, co-create joint solutions with partners, and provide enablement training for sales teams and ecosystem partners.

• Education: Bachelor's degree or higher in Computer Science, Software Engineering, or a related field.

• English Proficiency: Strong written and verbal English skills, capable of conducting in-depth technical exchanges and product solution discussions with international English-speaking clients.

• Experience: 5+ years of experience in the Big Data & AI domain, including at least 2 years in roles such as Solution Architect, Technical Consultant, or transitioning from a core R&D position.

• Distributed Computing Frameworks: Deep understanding of the principles, tuning, and applicable scenarios of core components including Hadoop, Spark, Flink, Presto/Trino, and Kafka.

• Data Architecture Evolution: Profound understanding and hands-on experience with Lambda architecture, Kappa architecture, and Data Lakehouse architecture, knowledgeable about compute-storage separation architecture design and cloud-based Big Data services (e.g., EMR, MaxCompute, Redshift).

• Data Storage & Format: Familiarity with object storage systems like HDFS, S3, and OSS, expertise in open table formats such as Parquet, ORC, Delta Lake, Iceberg, and Hudi.

• AI Infrastructure Hardware: Solid foundation in AI Infra hardware, including heterogeneous computing server architectures, high-performance networking, GPU/AI chips and interconnects, CPU/GPU/Memory/Storage access patterns, server networking topologies, multi-level storage system architectures, and their capability boundaries.

• AI Practical Skills: Hands-on capabilities in Python/Shell programming, invoking Large Language Model (LLM) SDKs, and utilizing mainstream open-source frameworks, product SDKs, or standardized services for ML/DL model inference, training, and deployment.

• Data Governance & Security: Familiarity with data lineage, metadata management, data quality monitoring, and privacy-preserving computation technologies.

• Business Acumen: Ability to comprehend customer business objectives (cost reduction, efficiency improvement, compliance, innovation) and design technical solutions accordingly. Candidates with proven records in building enterprise Big Data platforms and migrating on-premise data centers to Cloud are strongly preferred.

• Candidates must possess a professional customer service mindset, strong teamwork capabilities, the ability to translate complex technical concepts into clear business value for clients, and a commitment to excellence. They are expected to thrive in dynamic environments by actively facing and embracing change.