Project description

The role exists to rapidly deliver business-facing AI solutions for an Investment Bank, with a strong emphasis on quick ROI for traders and lending teams.
The initial focus is designing and building AI-powered tools (POCs/MVPs) that automate or augment work currently done by junior investment researchers, including:
• Researching documents, papers, websites, and internal/external data sources
• Synthesizing insights for traders and banking stakeholders
• Integrating AI capabilities into existing UBS platforms
This is not a pure R&D role success is measured by adoption, business impact, and speed to value.

Responsibilities

Business & Stakeholder Engagement

Work directly with traders, junior traders, and banking stakeholders

Translate business problems into AI use cases

Lead discovery, scoping, and requirement shaping for AI initiatives

Act as a bridge between business, data, and engineering

AI Solution Design & Delivery

Design and implement AI-driven POCs and MVPs with fast turnaround

Build AI agents / "avatars" capable of:

○ Researching structured and unstructured data

○ Calling external/internal APIs

○ Producing synthesized outputs for end users

Contribute to or extend existing AI platforms (e.g., MCP‑based services)

Technical Execution (Hands‑on)

Develop backend AI services and orchestration layers

Contribute to frontend integrations (React-based UIs)

Integrate LLMs, copilots, and AI tooling into enterprise platforms

Ensure solutions are secure, scalable, and production‑ready (where required)

POC‑to‑Scale Enablement

Support transition from POC → MVP → wider rollout

Define patterns, reusable components, and best practices

Mentor junior engineers/analysts as the team scales

Enable a "factory" model over time

Skills

Must have

AI & Engineering

Strong hands‑on experience with LLM‑based solutions

Experience building AI agents / assistants / copilots

Backend development experience (API‑driven architectures)

Familiarity with React or modern web frontends

Experience integrating multiple data sources and APIs

Understanding of AI orchestration layers (agent frameworks, MCP‑like patterns)

Cloud & Tooling

Experience in Microsoft/Azure AI ecosystem preferred

○ Copilot, Azure OpenAI, Azure AI services

Enterprise‑grade development practices (security, logging, governance)

Banking & Domain Knowledge

Investment Banking / Global Banking exposure

Lending, IB, or NCL (Non‑Core Lending) knowledge strongly preferred

Understanding how traders and banking teams consume insights

Communication & Consulting Skills

Strong verbal and written communication

Ability to engage confidently with traders

Business analysis and problem‑framing skills

Comfortable operating with incomplete requirements

Nice to have

Prior experience automating research or analyst workflows

Experience with:

○ Knowledge retrieval (RAG)

○ Document intelligence

○ Financial data platforms

Previous work in POC-heavy or innovation teams

Exposure to Tier‑1 banks

Other

Languages

English: C1 Advanced

Seniority

Senior

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Senior AI Engineer (Banking & Lending)

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