IntroductionAt 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 the Worldwide Client Engineering watsonx.data Leader, you'll harness your unique skills and perspectives to drive scale and productivity of watsonx.data pilots implemented by Client Engineering teams around the world, contributing to IBM's story of growth and innovation.
In this role, you'll partner with sales, product, development, research, and technical leaders across IBM to 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 prospective campaigns, demos, reusable pilot assets, and best practices that lead clients to continually investing in watsonx.data.
Your Role and ResponsibilitiesYou'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.
Your primary responsibilities will include:
- Proof of Concept (POC) Development: Develop POCs to validate and highlight 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.
- Collaboration and Project Management: Collaborate with cross-functional teams, including data scientists, software engineers, and project managers, to ensure smooth execution and successful delivery of AI solutions. Effectively communicate project progress, risks, and dependencies to stakeholders.
- Best Practices and Community Leadership: Establish and refine best practices around watsonx.data engagements, lead the corresponding watsonx.data Community of Practice.
- Solution Implementation and Deployment: Oversee the implementation and deployment of AI solutions, working closely with development teams to ensure adherence to best practices, quality standards, and performance requirements. Provide technical guidance and support during the implementation phase.
- Solution Optimization and Performance: Continuously monitor and optimize the performance of AI solutions, including foundation models and large language models. Identify opportunities to enhance efficiency, accuracy, and speed through fine-tuning, algorithmic improvements, or infrastructure optimization.
- 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- AI-Related Education: Possess an education background in Computer Science, Artificial Intelligence, Data Science, or a related field.
- Designing and delivering Data and AI solutions: With a focus on foundation models, large language models, exposure to open source, or similar technologies. Understanding of machine learning and deep learning algorithms. Experience with databases, data warehouses, data lakehouses, analytics, data engineering, ETL/batch and data quality, data stewardship, data security, data privacy and related topics.
- Strong programming skills: 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.
- Solutioning Experience: Solution architecture and design, translating business requirements into technical specifications, developing scalable and robust AI solutions.
- Business Acumen: Experience collaborating closely with customers, understanding their needs, business objectives, and translating their requirements into effective AI solutions.
- 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- Comprehensive familiarity with IBM's Offerings: Hands-on experience with any of IBM's data products and services (training across IBM's product suite will be provided).
