We're seeking someone to join our team as an AI Solution specialist to focus on rapidly design and build AI‑enabled prototypes and internal tools that improve business workflows, decision support, and operational efficiency. This role sits at the intersection of business, data, and technology translating ideas into working proof‑of‑concepts that can later be industrialized by Technology teams.

What you’ll do in the role:

• Design and build AI‑driven proof‑of‑concepts (POCs) and internal tools that address real business problems
• Develop rapid prototypes using Python, APIs, and structured data, with a focus on automation and workflow enhancement
• Integrate large language models (LLMs) into practical use cases such as document analysis, summarization, and internal advisory tools
• Build retrieval‑augmented generation (RAG) solutions that leverage internal knowledge sources to produce grounded, explainable outputs
• Partner closely with business stakeholders to refine requirements and with Technology teams to enable smooth handoff for production scaling
• Contribute to technical discussions around architecture, feasibility, and implementation trade‑offs

What you’ll bring to the role:

• Undergraduate or Master’s degree in Mathematics, Economics, Statistics, Finance, Computer Science, Engineering or a similarly quantitative field.
• At least 6 years of relevant experience. An equivalent combination of education and experience, and relevant competencies will be considered.
• Demonstrated experience applying quantitative methods to real‑world problems within or adjacent to the financial services industry.
• Hands‑on experience programming in Python (experience with Scala or MATLAB is a plus)
• Demonstrated ability to build working solutions from scratch, including personal, academic, open‑source, or commercial projects
• Practical experience integrating APIs and data sources into end‑to‑end applications
• Familiarity with LLM concepts, including prompt design, token usage, and cost awareness
• Ability to communicate technical ideas clearly to non‑technical stakeholders and strong problem‑solving skills and comfort working in ambiguous, fast‑moving environments