Data Architect - Generative AI Architect

IBM is evolving its technology sales approach with innovative methods, co-creating solutions with clients in real-time to address their business challenges. As a Data Architect - Generative AI in IBM's Client Engineering squad, you will contribute to the co-creation of Proofs of Value (PoV) and Minimal Viable Products (MVP) using Foundation Models, demonstrating the value of AI solutions. You will collaborate with Technical Leaders and Sales to drive client engagements, ensuring rapid delivery and product innovation.

In this role you can expect to have the responsibilities:

• Fine-tune pre-trained Foundation Models and assist stakeholders with analysis and implementation.
• Apply prompt-engineering techniques to specific use cases and models.
• Collaborate with clients to rapidly develop AI solutions using IBM Watson X Platform via a Proof of Experience (PoX).
• Apply Foundation Models to propose and validate hypotheses for business queries.
• Utilize the latest IBM AI technical strategies and sales plays to unlock client opportunities, applying AI development skills, model building, fine-tuning, and API integration.
• Grasp clients' business processes and challenges, employing statistical analysis skills to identify transformation opportunities.

This role requires you to have:

• Understanding of Foundation Models and experience deploying them for real-world examples.
• Knowledge of cloud technologies, specifically Kubernetes, for large-scale AI workloads.
• Ability to design, build, and validate successful AI solutions based on real-world cloud use cases.
• Demonstrated capability to evaluate AI solutions through experimental methods and prototype creation.
• Strong communication skills and effective collaboration within a local team.
• 5+ years of relevant experience.
• Excellent command of the English language, both verbal and written.
• Technical expertise in areas such as deployments and migrations to the cloud, open-source database deployments and migrations, data governance, data warehousing, systems design, training and fine-tuning models in large-scale environments, and experience with devops and CI/CD tool chains.
• Experience working in a customer-facing role, creating Data & Analytics Proof of Concepts (PoC) and Minimum Viable Products (MVP) for customers.

You would benefit from having:

• Strong contribution record in foundation models or large-scale machine learning models.
• Track record of collaborative problem solving.
• Knowledge of Large Language Models (LLM), Langchain, and HuggingFace Model.

Must have the ability to work in Canada without sponsorship.