Context Engineer

Royal Bank of Canada•Minneapolis, MN

1d•Onsite

About The Position

We are embedding GenAI into everyday workflows for Financial Advisors and operational teams—starting with simple, high-value prompt use cases and expanding into agent-enabled experiences. This role is a frontline builder. As a Context Engineer (Prompt Analyst), you will focus on creating high-quality saved prompts that advisors and teams use daily and supporting agent workflows by designing and refining the prompts and context that drive them. This is a new capability for the organization. You will play a critical role in proving how GenAI can deliver real, measurable productivity gains—quickly and safely.

Requirements

Experience working with GenAI tools (e.g., ChatGPT, Claude, or similar) in a hands-on, applied way
Demonstrated ability to write clear, structured prompts
Demonstrated ability to iterate based on output quality
Strong problem-solving skills with ability to break down business tasks into steps
Comfort working with both business stakeholders (advisors, operations) and technical teams (AI engineering, data)
Basic technical fluency: Understanding of APIs, structured data (JSON), or similar concepts
Ability to work in a fast-paced, test-and-learn environment

Nice To Haves

Exposure to prompt engineering techniques (few-shot, role prompting, structured outputs)
Exposure to agent frameworks or workflow automation tools
Background in financial services or wealth management
Experience with data analysis or business analysis
Experience with user experience or workflow design

Responsibilities

Build and Maintain Saved Prompts: Design simple, reusable prompts for internal AI tools (e.g., copilot-style usage), support high-frequency workflows such as client summaries and insights, meeting preparation and follow-ups, book of business reviews, and operational and service tasks. Ensure prompts are easy to use, consistent in output, and grounded in the right business context. Continuously refine prompts based on user feedback and observed performance.
Support Agent Prompt Development: Work with the Agent Lead and AI Engineering to build and test prompts used inside agent workflows, structure inputs and outputs for multi-step processes, and help improve how agents interpret instructions, use data and tools, and generate reliable responses.
Translate Business Needs into Effective Prompts: Partner closely with advisors and business teams to understand what they are trying to accomplish and where GenAI can help (and where it should not be used). Convert real-world workflows into clear prompt instructions and structured inputs and expected outputs. Apply wealth management context (clients, accounts, portfolios, compliance considerations).
Test, Evaluate, and Improve Output Quality: Run structured testing on prompts to evaluate accuracy and completeness, consistency across runs, and the risk of hallucination or misinterpretation. Identify failure patterns and refine prompts accordingly. Support lightweight evaluation approaches (prompt comparisons, A/B testing).
Contribute to Prompt Standards and Best Practices: Help document and maintain prompt templates and reusable patterns, provide guidance on when to use simple prompts vs. more complex solutions, and ensure prompts align with data privacy expectations, AI governance, and risk standards.