Job Description

Responsibilities

Generative AI Use Case Assessment Shaping
Collaborate with Business stakeholders and Business Analysts to identify define and prioritize Generative AI opportunities
Conduct frontend feasibility and scope assessments evaluating use case suitability data readiness risk considerations and value potential
Filter out misscoped or unfeasible requirements before AI engineering engagement ensuring clean and handovers

Generative AI Solution Research Design
Partner with Generative AI engineers to research design and refine AI solutions that address business needs
Research on the latest Generative AI trends emerging technologies and market best practices Contribute to enhancement to enterprise level AI frameworks playbooks and standards Incorporate industry best practices into model design evaluation and solution optimization
Analyze model and solution behaviors to identify limitations such as misinterpretations hallucinations edge case failures or inconsistent responses and collaborate with engineers to implement improvements
Stay informed on the latest Generative AI trends emerging technologies and market best practices contributing insights to guide development and continuous enhancement of AI solutions

Business Collaboration
Help Business Analysts and users during UAT for Generative AI solutions and advise business users on Generative AI solution behaviour and behaviour root cause
Work closely with Technology and AI Engineering teams to clarify issues formalize fixes and ensure solutions meet business intent and evaluation criteria

Machine Learning Advanced Analytics
Design and develop machine learning models for automation insights and use cases
Leverage enterprise machine learning platforms to build and deploy models effectively
Document model logic assumptions and limitations for transparency governance and knowledge sharing

Job Description - Grade Specific

Qualifications
Bachelors or Masters degree in Data Science Computer Science Artificial Intelligence Engineering Statistics or a related quantitative discipline
3-7 years of applied experience in AI machine learning analytics and Generative AI roles
Hands on experience with Generative AI solutions e.g. chatbots copilots LLM based tools agentic assistants in enterprise environments
Strong understanding of the end-to-end AI lifecycle including use case definition feasibility assessment evaluation and continuous improvement
Experience working in Agile delivery environments collaborating with product owners business analysts and technology teams

Preferred Skills
Generative AI Expertise Deep understanding of Generative AI models model behaviour and limitations and application frameworks with the ability to assess solutions and guide improvements
AI Solution Design Ability to translate business pain points into AI opportunities and propose solutions that balance speed to market cost and quality
Cloud Microsoft AI Stack Familiarity with cloud based AI platforms preferably within the Microsoft ecosystem eg Azure Copilot Studio AI Foundry with awareness of cloud and data constraints in Gen AI solution design
Agile Delivery Collaboration Experience to deliver UAT cycles and sprint based refinement with Business BAs and Technology teams
Banking Enterprise Context Understanding of banking products operating models and regulatory considerations with the ability to assess GenAI use cases in a regulated enterprise environment
Communication Stakeholder Engagement Strong ability to clearly convey AI capabilities risks and recommendations to both technical and nontechnical stakeholders'