Customer Success Engineering - Data & AI (French speaking)/Ingénierie du succès client - Données et IA (francophone)

Introduction

At IBM Global Sales, we bring together innovation, collaboration, and expertise to help clients solve their most complex business challenges. Working across industries and geographies, you’ll partner with colleagues, clients, and partners to co-create solutions that drive digital transformation and lasting impact.Success in Global Sales is built on curiosity, empathy, and collaboration. You’ll connect technical understanding with strong people skills, building trusted relationships and shaping solutions that improve business and society. With world-class onboarding, continuous learning, and a supportive culture, IBM offers the tools and opportunities to grow your career. Join us and be part of a global team that’s passionate about driving innovation and making a difference.

Your Role And Responsibilities

As a Customer Success Engineer, you will design viable client solutions by leveraging current product capabilities and remove technical inhibitors to sales opportunities. You will work with clients to drive adoption and expansion of IBM products to accelerate client value. Your primary responsibilities will include:

• Deliver Technical Proof Points: Create and deliver technical proof points through technical accelerators, such as demonstrations, POTs, POCs, Workshops, Solution Design, and MVPs, to demonstrate the value of IBM products to clients.
• Drive Customer Value: Activate entitlements by finding sponsors, conducting use-case workshops, and establishing measurable business outcomes with client sponsors and stakeholders.
• Develop Success Plans: Create a success plan that describes deployment roadmap(s), milestones, and outcomes with client sponsors and stakeholders to ensure successful adoption and expansion of IBM products.
• Understand Client Challenges: Deeply understand clients' main challenges and become a trusted guide for their modernization and adoption of IBM's technology portfolio.

Preferred Education

None

Required Technical And Professional Expertise

• Exposure to Technical Solution Design: Experience working with current product capabilities to design viable client solutions and remove technical inhibitors to sales opportunities.
• Technical Accelerators Knowledge: Familiarity with creating and delivering technical proof points through technical accelerators, such as demonstrations, POTs, POCs, Workshops, Solution Design, and MVPs.
• Understanding of Client Value Drivers: Exposure to working with clients to drive adoption and expansion of products to accelerate client value.
• Familiarity with Success Planning: Experience working with clients to develop a success plan that describes deployment roadmap(s), milestones, and outcomes.
• Understanding of Client Challenges: Exposure to understanding clients' main challenges and identifying opportunities for modernization and adoption of new technologies.

Preferred Technical And Professional Experience

• Core Expertise
• Agentic SDLC concepts and frameworks
• Machine Learning, Generative AI, foundation models, and tuning (Prompt Engineering, RAG, etc.).
• Data warehouse or lakehouse architecture, Presto, and Iceberg formats.
• Data and AI gorvernance, lifecycle management, compliance, and risk mitigation.
• Technical Skills & Languages

A modern IBM CSE needs to be technical to solve business problems.

• Languages: Proficiency in Python (specifically for data science libraries like Pandas, Scikit-learn, and PyTorch).
• Data Architecture: Expert knowledge of SQL, NoSQL, and Vector Databases (e.g., Milvus).
• Cloud & Infrastructure: Experience with Red Hat OpenShift (the backbone of IBM’s hybrid cloud) and containerization (Docker/Kubernetes).
• DevOps/MLOps: Understanding the CI/CD pipeline for machine learning models.
• Solution Architecting & Methodology

It’s not just about knowing the tool; it’s about solving the business problem.

• Proof of Concept (PoC) Leadership: Ability to define success criteria, build a minimum viable product (MVP), and present the value-add to stakeholders.
• Hybrid Cloud Strategy: Understanding how to deploy solutions and IBM tools across AWS, Azure, and On-Prem environments.
• Sales Acumen
• Opportunity Identification : having experience reaching out to known and unknown contacts to identify new areas of value creation for customers.
• Opportunity progression :understanding and participated in the steps required by both a customer and a provider to sign an agreement i.e. close a deal.