**Introduction** We are seeking a Data Platform Partner Technical Specialist (PTS) to join our team in China. This role is instrumental in driving the success of our partner ecosystem by providing technical expertise and pre-sales support for our cutting-edge solutions. As a technical sale within IBM’s Data Platform brand, you’ll work at the intersection of business and technology, collaborating with IBM’s world-class teams and our partner ecosystem to deliver high-impact, scalable data and AI and solutions that help our clients lead in their industries. This role is particularly focused on clients and partners in the automotive, manufacturing, retail, and multinational enterprise sectors—where complex data landscapes and industry-specific needs demand deep domain understanding and tailored solutions. **Your role and responsibilities** Key Responsibilities As a Partner Technical Specialist, you will play a key role in driving the adoption of IBM’s Data & AI technologies by influencing and embedding our solutions within the technical strategies of customers, business partners, and service providers. Your success lies in your ability to build trust, simplify complexity, and co-create value through joint technical engagements. Your primary responsibilities include: · Technical Strategy Influence: Shape the technical strategies of clients and partners by aligning IBM’s technology with their long-term goals, reference architectures, and solution roadmaps. · Joint Solution Development: Collaborate with partners to design and implement joint solutions that integrate IBM’s Data & AI offerings, enhancing their technology stack and market differentiation. · Client Engagement & Enablement: Develop strong relationships with customers, understand their business and technical needs, and demonstrate how IBM’s industry-leading solutions address their challenges and drive measurable outcomes. · Credibility & Trust Building: Establish technical thought leadership and trust by delivering clear, value-focused guidance and facilitating the closure of complex cloud and AI solution deals. · Education & Evangelism: Lead proof-of-concepts (PoCs) and Proof-of-Technology (PoT) engagements, translate complex technical topics into simple business value, and upskill partner and client technical teams. · Ecosystem Enablement: Strengthen the technical capabilities of business and service partners to help them scale IBM-powered solutions effectively in the market. Co-Selling Acceleration: Create and support co-selling opportunities by connecting IBM’s internal experts, partner teams, and end clients to drive successful solution adoption and revenue growth. **Required technical and professional expertise** At least 3 years of practical experience implementing Data and AI solutions, including IBM and non-IBM technologies; 5 years preferred. 1. Cutting-Edge Data Architecture (Lakehouse, Data Fabric) · Design and optimize next-generation data ecosystems that unify transactional and analytical workloads using Lakehouse architectures (e.g., Delta Lake, Databricks). · Implement Data Fabric strategies to enable seamless data discovery, governance, and orchestration across hybrid and distributed environments. · Apply these frameworks within complex industry contexts such as automotive supply chains, manufacturing process optimization, retail customer intelligence, and multinational data compliance. 2. Deep ML, Foundation Models & AI Agents Expertise · Lead end-to-end model lifecycle—from rapid prototyping in TensorFlow, PyTorch, etc, to deploying cutting-edge techniques such as NLP, Vision Transformers, and LLMs (Large Language Models). · Apply and customize foundation models (e.g., open-source or proprietary) for specific use cases like predictive maintenance in manufacturing, virtual assistants in retail, and multilingual document analysis in global enterprises. · Explore and integrate autonomous AI agents for tasks such as intelligent workflow orchestration, customer engagement automation, or decision support—tailored to sector-specific needs. 3. MLOps & AI Lifecycle Automation · Build and maintain CI/CD pipelines with tools like MLflow, Kubeflow, or watsonx, ensuring scalable, automated retraining, monitoring, and governance of models in production. · Drive consistent business impact through repeatable, measurable, and maintainable AI deployments across industries. 4. Cloud-Native & Scalable Infrastructure · Architect and deliver scalable AI solutions using AWS, Azure, Google Cloud, or IBM Cloud, RedHat Openshift，leveraging microservices, Docker, Kubernetes, and Terraform for infrastructure-as-code. · Employ DevOps and DataOps best practices to accelerate deployment cycles, reduce technical debt, and ensure production-grade reliability. 5. Hands-On Innovation & Consultative AI Solutioning · Rapidly prototype proof-of-concept (PoC) and proof-of-technology (PoT) demos that address real-world industry challenges—such as automotive digital twins, manufacturing line intelligence, or omni-channel retail insights. · Translate complex AI and data capabilities into compelling, outcome-driven narratives that resonate with both technical and business stakeholders. Act as a trusted advisor to C-suite and technical teams, aligning solutions with enterprise strategy, unlocking new value streams, and driving digital transformation across automotive, manufacturing, retail, and multinational enterprise clients. IBM is committed to creating a diverse environment and is proud to be an equal-opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, gender, gender identity or expression, sexual orientation, national origin, caste, genetics, pregnancy, disability, neurodivergence, age, veteran status, or other characteristics. IBM is also committed to compliance with all fair employment practices regarding citizenship and immigration status.