Prompt Engineer

Job summary

Design and optimize AI prompts and workflows to enhance decision-making across Capital Markets and Commercial Banking functions. Manage a centralized prompt library and ensure AI outputs align with regulatory requirements and enterprise data.

Job details

Downtown Toronto | Hybrid, 2 days onsite | 6-month contract, expected to extend 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 Must Have Skills: 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 Nice to Have Skills: Microsoft ecosystem experience (Fabric, Power Platform, Graph API integration, etc) Amazon Bedrock Agentcore experience Relevant postsecondary degree

What you’ll do

Design and optimize AI prompts and workflows to enhance decision-making across Capital Markets and Commercial Banking functions. Manage a centralized prompt library and ensure AI outputs align with regulatory requirements and enterprise data.

Requirements

Requires over 3 years of experience in Capital Markets/Commercial Banking and at least 1 year of hands-on prompt engineering for LLMs. Proficiency in RAG pipelines, financial data analysis, and the ability to translate complex banking workflows into AI interactions is essential.

Listed skills

• Regulatory Compliance · Preferred
• Data analysis · Preferred
• prompt engineering · Preferred

Other relevant skills

Identified from the job description. Confirm important requirements above.

• Prompt Engineering
• Capital Markets
• Commercial Banking
• LLMs
• RAG Pipelines
• Vector Search
• Agentic Workflows
• Credit Adjudication
• Data Analysis
• Microsoft Fabric
• Financial Risk Metrics
• Copilot
• GenAI Platforms
• Business-to-Technology Translation
• Regulatory Compliance
• Prompt Optimization

Job areas

• Technology
• Finance & Accounting
• Data & Analytics
• Software
• Engineering