Customer Success Manager -Brand Specialist – Entry Level Sales Program 2026

Introduction

A Customer Success Manager Architect (CSM) focused on Artificial Intelligence (AI) in IBM means a career

where you're helping clients fully realize the value of their existing AI products, whilst growing their adoption

of next-generation technologies from across IBM's wider portfolio.

Preferring to 'show' vs. 'tell' we're looking for recent college graduates who want to combine their technical

interests and education with the people skills needed to architect technical solutions, co-creating with

customers, partners, and colleagues to solve technical and business challenges.

Excellent onboarding training will set you up for success, whilst ongoing development will continue to advance

your career through its upward trajectory. Our sales environment is fast-paced and supportive. Always part of

a team, you'll be surrounded by leaders and colleagues who are always willing to help and be helped – as you

support pilots that compel clients to invest in IBM's products and services.

Your Role And Responsibilities

The Customer Success Manager AI role in IBM has unique attributes. In addition to the people skills often

associated with this position, this AI CSM role is specialized in data science, generative AI, and large language

models. You will work closely with customers, product managers, and development teams to understand

client business requirements and implement AI solutions that address complex business challenges.

With a hands-on approach to coding, demonstrations, and clear communication, you will be able to showcase

IBM Ai solutions. You will design and articulate AI architectures compatible with a client’s technology stack

via use-case identification, solution architecture design, and MVP (minimal viable product) builds.

With technical expertise and a consultative style, you'll quickly build credibility as a trusted advisor at all levels

with customers and IBM colleagues. To drive expansion and renewal growth, you'll guide leading enterprise

companies through AI approaches that realize the full value of expanding their adoption of watsonx.

Your primary responsibilities will include, but not be limited to:

• Understanding Client's Data and AI Challenges and Building Trust: Understand clients' primary Data
  
  

and AI challenges and establish yourself as a trusted technical expert for their migration, deployment,

and adoption of AI and Hybrid Cloud offerings.

• Facilitating Use Case Exploration and Business Framing: Lead use case exploration and business
  
  

framing workshops, develop client value realization models.

• Developing AI Solutions: Using your Data and AI engineering skills to code/ build MVPs using python,
  
  

open-source frameworks, RedHat and IBM watsonx.

• 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 customer success plans aimed at
  
  

continually increasing active user adoption of IBM's products.

To Be Successful In This Role, You Will Need

• Confidence to contact and engage potential new customers and deliver an elevated experience.
• A desire to continually learn new technologies and how to apply their value in a client environment.
• Motivation to achieve technical objectives and high client satisfaction.
• Embrace curiosity and a growth mindset.
  
  

You may work with any of the following technologies: Data, Artificial Intelligence, IT Automation, Cloud,

Security,

This position requires you to be in one of the following IBM offices: Atlanta GA, Austin, TX, Boston MA, Chicago

IL, Dallas TX, New York NY, Raleigh NC, San Francisco CA, and Washington DC.

Approximately 25% travel may be required in this role, based on client needs and needs of the business.

IBM will not be providing visa sponsorship for this position now or in the future. Therefore, in order to

be considered for this position, you must have the ability to work without a need for current or future visa

sponsorship.

Preferred Education

Bachelor's Degree

Required Technical And Professional Expertise

Technical Education: B.S./M.S. in Computer Science, Artificial Intelligence, Data Science,

Engineering, Information Systems, or equivalent technical degree/experience.

• Programming Language: Experience with Python notebooks.
• AI Skills: Experience in Machine Learning, Deep Learning, Large Language Models.
• Proficiency in Python and ML toolchains (NumPy, Pandas, Scikit-learn, Jupyter) to prototype models and data
  
  

pipelines.

• Hands-on experience with model deployment (e.g. serving Hugging Face models via APIs) and LLM inference
  
  

(batch vs. real-time).

• Understanding of model fine-tuning and in-context learning (choosing when to prompt-engineer vs. train) as
  
  

part of the LLM lifecycle.

• Specialized Agentic AI frameworks: LangChain, LlamaIndex
• Experience in designing and implementing AI Agents for end users, while capturing non-functional requirements is
  
  

Preferred

• Deep Learning Frameworks: PyTorch, TensorFlow (including Keras) , Hugging Face transformers
• Vector Databases: Experience with vector stores like Pinecone, Weaviate, Milvus
• Client Focused: Asks open-ended questions and understands needs to address business challenges.
• Tech Savvy: Conversant about technology, latest industry trends and how it is being applied to
  
  

address business challenges.

• Team Player: Demonstrates team collaboration and can navigate different communication styles.
• Excellent Communication Skills: Possess verbal, written, and interpersonal skills that are engaging,
  
  

compelling and influential.

• Self-Motivation and Problem-Solving Aptitude: A natural inclination toward self-motivation and
  
  

initiative, in addition to the ability to navigate data and people to find answers and present solutions.

Preferred Technical And Professional Experience

• Familiarity with agile development methodologies.
• Knowledge of AI and data governance.
• Knowledge of generative AI architectures such as RAG, chatbots.
• Experience with RedHat OpenShift and Kubernetes.