AI Product Management

RBC•New York, NY

4d•$120,000 - $225,000•Onsite

About The Position

The AI & Digital Innovation team in RBC Capital Markets is seeking an AI Product Manager with expertise in product management for AI and data products, applied AI, Generative AI, and quantitative fluency for pricing and trading contexts to collaborate with Sales & Trading and develop desk-facing solutions. You will work across how sales understand clients, how sales and traders set a price, and how that price drives a sale, leading how these initiatives are framed, prioritized, built, and governed.

Requirements

5+ years of experience delivering AI, analytics, or data products for professional users in a capital markets or similarly regulated setting.
A demonstrated record of converting unstructured stakeholder requests into scoped, testable problem definitions with clear success criteria, and taking them through to a defined, evaluated, and adopted capability, with initiative and end-to-end ownership.
Experience prioritizing competing requests from multiple business and technology stakeholders, and aligning them on scope, sequencing, and acceptance criteria.
Demonstrated experience applying product management practices such as discovery, roadmap ownership, acceptance criteria, and adoption measurement.
Applied AI and Generative AI fluency sufficient to earn the confidence of engineering and data science partners, including evaluation, reliability, and known limitations. Building models is not part of this role.
Quantitative comfort with pricing, trading, and risk concepts, and the ability to work credibly alongside quantitative stakeholders.
Strong written and verbal communication with senior stakeholders, including concise framing of options, trade-offs, and recommendations.
Understanding of Sales & Trading workflows within Capital Markets

Nice To Haves

A post-secondary degree in a STEM discipline, Quantitative Finance, Economics or a related quantitative field, or equivalent hands-on technical experience.
Experience delivering AI or data products in a regulated or security-conscious environment, including exposure to model risk, compliance, or AI governance processes.
Exposure to electronic trading, automated pricing, or predictive analytics initiatives.
Risk concepts, market microstructure, and quantitative finance fluency for pricing, trading and risk-management contexts.

Responsibilities

Identify and prioritize desk-facing applied AI opportunities for Sales & Trading, with an emphasis on improving how sales understand clients, how sales and traders set a price, and how that price drives a sale.
Frame ambiguous commercial questions as scoped, testable product definitions, translating business needs and desk context into opportunities that can be evaluated, delivered, and adopted by real users.
Own the product roadmap and sequencing across initiatives, with an emphasis on explicit prioritization, documented trade-offs, and shared delivery expectations with business stakeholders and delivery partners.
Act as the bridge between the desk and engineering, data science, and quantitative partners, with an emphasis on agreed problem definitions, acceptance criteria, and evidence that a capability works for the users it is built for.
Drive adoption of delivered capabilities and learn from real user feedback after release, with an emphasis on observed needs, usability, reliability, and increasing practical value for Sales & Trading stakeholders.
Carry initiatives through risk, compliance, and AI governance, ensuring control, documentation, and human oversight expectations are understood early and met before a capability reaches users.