Product Owner - Senior

Position: Product Owner – Senior

Location: Toronto ON - Hybrid

Duration: 6 months Contract

Role Title: Prompt Engineer

Line of Business: T&O

Hybrid work requirements: 2x/week in office

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

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