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Introduction

A Customer Success Manager Architect (CSM) career in IBM means a career where you're helping clients fully realise the value of their existing IBM products, whilst growing their adoption of next-generation technologies from across IBM's wider portfolio. It means being a trusted strategic advisor to some of the world's most transformational enterprises and culturally influential brands, as they rely on your expertise and our technology to solve some of their hardest problems. Excellent onboarding and an industry leading learning culture will set you up for positive impact and success, whilst ongoing development will advance your career through an upward trajectory. Our sales environment is collaborative and experiential. Part of a team, you'll be surrounded by bright minds and keen co-creators – always willing to help and be helped – as you apply passion to work that will have a positive impact to the world around us.

Your role and responsibilities

A Customer Success Manager opportunity in IBM might be different to what you're used to. In addition to the people and commercial skills often associated with this position, an IBM CSM is also an Architect. Someone with a deep understanding of technical complexities. A person who can quickly understand clients' hard-to-understand technology issue and communicate them back in an easy-to-understand way. With deep roots in a hands-on technological background, and through different communication techniques, you'll be able to showcase IBM solutions. Using excellent communication, you'll articulate their compatibilities with a client's stack via use-case identification, solution architecture design, and MVP builds. With technical expertise and a consultative style, you'll quickly build credibility as a trusted advisor at all levels. To drive expansion and renewal growth, you'll guide IT executives through the changes needed to realise the full value of expanding their adoption of IBM's products. Your primary responsibilities will include: Understanding Client's Challenges and Building Trust: Understand clients' primary challenges and establish yourself as a trusted technical expert for their migration, deployment, and adoption of Hybrid Cloud and AI Growth offerings. Facilitating Use Case Exploration and Business Framing: Lead use case exploration and business framing workshops, develop client value realization models. Leading Persuasive Technical Conversations: Lead technical discussions that persuade clients to act based on their requirements and the value provided by IBM's solutions. Creating Post-Deployment Customer Success Plans: Develop post-deployment customer success plans aimed at continually increasing post-launch, active user adoption of IBM's products.

Required education

Bachelor's Degree

Preferred education

Bachelor's Degree

Required technical and professional expertise

• Proven Expertise in Data Technologies: Strong background in data platforms, data management, and analytics, with hands-on experience in designing, implementing, or supporting data-driven solutions.
• Experience in AI and Data-Driven Solutions: Practical knowledge of AI technologies, including machine learning and generative AI, with an understanding of how AI enhances data utilization and decision-making.
• Cloud and Hybrid Data Architecture Understanding: Proficiency in cloud-based and hybrid data architectures, with experience in platforms such as AWS, Azure, Google Cloud, or IBM Cloud.
• Agile and Problem-Solving Mindset: Ability to apply agile methodologies to data-related projects and a strong aptitude for problem-solving, navigating complex technical challenges efficiently.
• Effective Communication and Client Engagement: Proven ability to articulate complex data concepts to both technical and non-technical stakeholders, fostering strong relationships from engineers to executives.

Preferred technical and professional experience

• Broad Experience in Data and AI Solutions: Familiarity with various data and AI technologies, including data engineering, machine learning, and AI-powered analytics.
• Understanding of Enterprise Data Ecosystems: Experience working with enterprise data architectures, including data lakes, data warehouses, and data integration frameworks.
• Knowledge of Data Security and Compliance: Awareness of data security best practices, governance, and regulatory compliance frameworks relevant to enterprise data management.