
Customer Success Engineer Co-op Fall 2026
IBM · San Francisco, CA
- On site
- Full-time
- $45,000 / year
- San Francisco, CA
Job highlights
- Help clients adopt next-gen IBM technologies, including AI.
- Co-create technical solutions with customers and colleagues.
- Develop and deploy AI solutions using Python and frameworks.
- Build trust as a technical advisor with enterprise clients.
- Increase adoption of IBM products and services.
About the role
Customer Success Engineer Co-Op - Fall 2026
A Customer Success Engineer (CSE) focused on IBM solutions means a career where you're helping clients fully realize the value of their existing products, whilst growing their adoption of next-generation technologies from across IBM's wider portfolio, including AI. This is a 16-week Co-Op position for actively enrolled undergraduate or graduate university students who are graduating between May 2027 and May 2028. Must be eligible and available for full-time work (40 hours a week) during the fall semester 2026. Students should not be enrolled in classes while working this Co-op.
We're looking for undergraduate and graduate students 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.
IBM’s Sales Co-Op Program culture 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
A Customer Success Engineer Co-Op role at IBM has unique attributes. In addition to the people skills often associated with this position, in this CSM Co-Op role, you will work closely with customers, product managers, and development teams to understand client business requirements and implement solutions that address complex business challenges. You'll learn to co-create with colleagues and clients to deliver the engine that sits at the center of their digital transformation's success.
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 are not 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, and Security.
This is a full-time, on-site position located in one of the following IBM offices: Brookhaven, GA, Chicago, IL, Dallas, TX, New York, NY, San Francisco, CA, and Washington, DC. Readiness to travel, if needed.
Required Technical And Professional Expertise
- Actively Enrolled: Registered undergraduate or graduate university student eligible and available for full-time work (40 hours a week) during fall semester 2026. Students should not be enrolled in classes while working this Co-op.
- Technical Education: Seeking B.S. or M.S. degree 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
- 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.
Key skills/competency
- Customer Success Engineering
- AI Solutions
- Python
- Machine Learning
- Deep Learning
- Large Language Models
- Data Science
- Cloud Computing
- Technical Consulting
- Client Relationship Management
Skills & topics
- Customer Success Engineer
- Co-op
- Fall 2026
- IBM
- AI
- Python
- Machine Learning
- Data Science
- Cloud
- Technical Sales
- Computer Science
- Engineering
- Student
- Internship
How to get hired
- Tailor your resume: Highlight Python, AI/ML skills, and co-op experience for IBM's Customer Success Engineer role.
- Showcase technical projects: Detail your experience with AI frameworks, data pipelines, and model deployment in your application.
- Demonstrate client focus: Emphasize your communication, problem-solving, and ability to understand business challenges.
- Prepare for technical interviews: Be ready to discuss AI concepts, Python coding, and how you'd architect solutions.
- Understand IBM's values: Align your application with IBM's focus on innovation, client success, and teamwork.
Technical preparation
Behavioral questions
Frequently asked questions
- What are the eligibility requirements for the IBM Customer Success Engineer Co-op?
- To be eligible for the IBM Customer Success Engineer Co-op (Fall 2026), you must be an actively enrolled undergraduate or graduate university student graduating between May 2027 and May 2028. You must be available for full-time work (40 hours/week) during the fall semester 2026 and not enrolled in classes during the co-op period.
- What technical skills are most important for this IBM Co-op role?
- Key technical skills for this IBM Co-op include Python programming, experience with AI and Machine Learning (ML) concepts, proficiency in ML toolchains like NumPy, Pandas, and Scikit-learn, and familiarity with deep learning frameworks (PyTorch, TensorFlow) and specialized AI frameworks (LangChain, LlamaIndex). Experience with model deployment and vector databases is also beneficial.
- What kind of projects will a Customer Success Engineer Co-op work on at IBM?
- As a Customer Success Engineer Co-op at IBM, you will work on projects that involve understanding client data and AI challenges, exploring use cases, developing AI solutions (MVPs) using Python and IBM watsonx, leading technical conversations, and creating post-deployment customer success plans to drive product adoption.
- Is the IBM Customer Success Engineer Co-op a remote or on-site position?
- The Customer Success Engineer Co-op position at IBM is a full-time, on-site role. You will be located in one of the specified IBM offices: Brookhaven, GA, Chicago, IL, Dallas, TX, New York, NY, San Francisco, CA, or Washington, DC.
- What is the duration of the IBM Customer Success Engineer Co-op?
- The IBM Customer Success Engineer Co-op is a 16-week position, specifically scheduled for the fall semester of 2026.
- How can I demonstrate my 'client-focused' aptitude for this IBM co-op role?
- To demonstrate your client-focused aptitude, highlight experiences where you've asked open-ended questions to understand needs, solved business challenges through technical solutions, and communicated complex ideas effectively. Mention any projects or coursework where you collaborated with others to achieve a common goal.
- What kind of career growth can be expected after an IBM Sales Co-op program?
- IBM's Sales Co-op Program is designed to set you up for success with ongoing development to advance your career. The fast-paced and supportive sales environment, combined with team collaboration, provides a strong foundation for upward career trajectory within IBM.