Client Engineering - AI Engineer

Introduction
Introduction: At IBM we’re revolutionizing our approach to technology sales. Our Client Engineering teams are champions of co-creating solutions in real-time to solve complex business challenges.
As an AI Engineer within our Client Engineering team you’ll harness your unique skills and perspectives to engage in the development and deployment of AI systems using our watsonx platform creating 4-to-6-week pilots for clients and contributing to IBM’s story of growth and innovation.
In this role you’ll partner with technical leaders across IBM and drive client engagements with a curiosity that sparks innovation and learning. Your contributions will form a cornerstone in our sales strategy facilitating rapid client delivery and product innovation.
At IBM the possibilities are endless. We offer extensive onboarding and ongoing development fostering an environment where you can thrive and shape your own career trajectory. Surrounded by a supportive team you’ll be integral in creating user-centric compelling pilots that lead clients to continually invest in IBM’s people products and services.

Your Role and Responsibilities
An AI Engineer at IBM is not just a job title – it’s a mindset. You’ll leverage the watsonx platform to co-create AI value with clients focusing on technology patterns to enhance repeatability and delight clients.
Success is our passion and your accomplishments will reflect this driving your career forward propelling your team to success and helping our clients to thrive.

Day-to-Day Duties:

• Proof of Concept (POC) Development: Develop POCs to validate and showcase the feasibility and effectiveness of the proposed AI solutions. Collaborate with development teams to implement and iterate on POCs ensuring alignment with customer requirements and expectations.
• Customer Engagement and Support: Act as a technical point of contact for customers addressing their questions concerns and feedback. Provide technical support during the solution deployment phase and offer guidance on AI-related best practices and use cases.
• Documentation and Knowledge Sharing: Document solution architectures design decisions implementation details and lessons learned. Create technical documentation white papers and best practice guides. Contribute to internal knowledge sharing initiatives and mentor new team members.
• Industry Trends and Innovation: Stay up to date with the latest trends and advancements in AI foundation models and large language models. Evaluate emerging technologies tools and frameworks to assess their potential impact on solution design and implementation.

Required Technical and Professional Expertise

• Education: Bachelor’s Master’s or Ph.D. degree in Computer Science Artificial Intelligence Data Science or a related field.
• Technical Skills: Strong programming skills with proficiency in Python and experience with AI frameworks such as TensorFlow PyTorch Keras or Hugging Face. Understanding in the usage of libraries such as SciKit Learn Pandas Matplotlib etc. Familiarity with cloud platforms (e.g. Kubernetes AWS Azure GCP) and related services is a plus.
• Soft Skills: Excellent interpersonal and communication skills. Engage with stakeholders for analysis and implementation. Commitment to continuous learning and staying updated with advancements in the field of AI.
• Growth mindset: Demonstrate a growth mindset to understand clients’ business processes and challenges.

Preferred Technical and Professional Expertise
Experience:

• Proven experience in designing and delivering AI solutions with a focus on foundation models large language models exposure to open source or similar technologies.
• Experience in natural language processing (NLP) and text analytics is highly desirable.
• Understanding of machine learning and deep learning algorithms.