Prompt Engineer

Role Title: Prompt Engineer Ideal Start date: Nov 1, 2026 Contract duration: 6 months Extension likelihood: yes OT requirements: not anticipated Hybrid work requirements: 2x/week in office Role Mandate: The role is responsible for designing, optimizing, and operationalizing AI prompts and workflows that power decision-making across Capital Markets and Commercial Banking functions, including Trading, Corporate Banking, Credit Structuring, Research, Risk, and Operations. This role bridges front-office business needs and AI-driven insights, ensuring AI platforms deliver accurate, timely, and context-aware outputs aligned with market dynamics, regulatory requirements, and enterprise data. By developing a deep understanding of bankers’ day-to-day workflows, the Prompt Engineer creates curated, workflow-specific prompts and AI experiences that improve productivity, streamline processes, accelerate analysis, and enhance client service. The role also owns the design, governance, and continuous improvement of a centralized prompt library, providing reusable, scalable, and business-aligned prompt assets that drive consistent AI outcomes, promote best practices, and accelerate adoption across the organization. Team Structure: Sole position reporting to HM, mostly independent but collaborative with stakeholders in Corporate Banking and broader Capital Markets. Role Responsibilities: AI Prompt Engineering for Capital Markets (Corporate Banking, Global Markets, Investment Banking) and Commercial Banking • Design and optimize prompts for use cases across trading desks, sales workflows, research generation, pricing analytics, and risk reporting • Tailor prompts for persona-specific needs (e.g., traders, sales, quants, risk managers) Business-to-AI Translation • Translate complex Capital Markets workflows (trade lifecycle, credit adjudication, pricing, P&L, exposure) into effective AI-driven interactions • Enable AI to generate insights on market events, positions, client portfolios, and trade opportunities AI-Driven Decision Enablement • Ensure AI outputs are context-aware (market data, client context, regulatory constraints) and decision-ready • Enable scenario analysis, trade recommendations, and risk insights using AI workflows Integration with Enterprise Data & Platforms • Leverage structured and unstructured data (market feeds, trade data, research, client notes) • Integrate prompts with Microsoft Fabric, Graph, Dataverse, and trading/risk systems • Support RAG-based architectures for research and knowledge retrieval Continuous Optimization & Performance Tuning • Evaluate prompt performance using real trading scenarios • Iterate using feedback from traders, sales, and risk teams • Improve precision, latency, and reliability of AI outputs Governance, Compliance & Responsible AI • Ensure AI outputs comply with Capital Markets and Commercial Banking regulations (e.g., trade surveillance, auditability, model risk) • Embed guardrails for data privacy, explainability, and approval workflows • Align with enterprise AI governance and model validation standards Adoption & Enablement • Develop reusable prompt libraries for trading, research, and sales workflows • Train front-office and middle-office teams on effective AI usage • Drive adoption of AI-assisted workflows across Capital Markets and Commercial Banking Key Competencies • Market-Aware Analytical Thinking – Ability to interpret market movements and translate them into AI use cases • Structured Problem Solving – Breaking down complex trading workflows into AI-driven components • Business-to-Technology Translation – Converting front-office needs into scalable AI solutions • Decision-Oriented Communication – Delivering clear, actionable AI outputs for time-sensitive decisions • Continuous Learning & Adaptability – Keeping up with evolving AI capabilities and market changes • Precision & Risk Awareness – Ensuring high accuracy in AI outputs in a high-stakes financial environment Qualifications • Strong experience (3+ years) in Capital Markets and Commercial Banking Sales, including but not limited to credit adjudication, AML/KYC, trading, investment products etc. • Understanding of credit adjudication lifecycle, product offerings, pricing models, P&L, risk metrics (VaR, sensitivities), and regulatory controls • 1+ year of hands-on experience designing prompts for LLMs / Copilot / GenAI platforms • Experience with RAG pipelines, vector search, embeddings, and agentic workflows • Strong data analysis skills (structured + unstructured datasets) • Familiarity with market data sources and financial datasets • Ability to work closely with traders, bankers, risk managers, and technology teams • Strong communication and translation across business and technology Core Skills • Microsoft ecosystem experience (Fabric, Power Platform, Graph API integration, etc) • Amazon Bedrock Agentcore experience • Relevant postsecondary degree Interviews: 1 round, 45 min with HM and team member(s)