Job Title: Prompt Engineer (GenAI – Capital Markets)

Line of Business: T&O;

Ideal Start date: Nov 1, 2026

Contract duration: 6 months with possible extension

Working hours: 8:30am-5pm

Office location: 100 King St W, Toronto ON- Hybrid work requirements: 2x/week in office

Team Structure: Sole position reporting to HM, mostly independent but cooperative with stakeholders in Corporate Banking and broader Capital Markets.

Interviews: 1 round, 45 min with HM and team member(s)

Ideal Match: A Capital Markets / Commercial Banking professional who has hands-on GenAI/Prompt Engineering experience , especially someone who has worked on RAG + LLM + agentic workflows in a banking environment .

Big plus: Microsoft Fabric, Copilot, Power Platform, Graph API/Dataverse, financial/market data, or Amazon Bedrock AgentCore experience.

In one line:

? Banking/Capital Markets expertise + real hands-on GenAI/Prompt Engineering = ideal candidate.

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.

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

📌 Prompt Engineer (Greater Toronto Area)
🏢 SPECTRAFORCE
📍 Greater Toronto Area