JPMorgan paying $200k salaries to teach bankers prompt engineering
JPMorgan is more keen on generative AI hiring than most other banks. It's not only hiring AI scientists or engineers, however; the bank is building out a team that's more inclined on hiring consultants.
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JPMorgan currently has several openings in its Gen AI enablement team, within the commercial and investment bank (CIB) based in New York and London. They state that the focus of the team is to identify the most important AI use cases and to influence the product roadmap. The team appears to be run by Allie Gillon-Livesey, head of CIB GenAI strategy. Gillon-Livesey is based in London and assumed the role last January after working on strategic partnerships in the CIB chief data and analytics office.
The AI enablement roles range from associate to executive director. Each advertisements states that expereince at a "top strategy consulting firm" is preferred. Openings at VP and executive director level each request a degree similar to computer science; a STEM degree is only optional for the associate role.
Prompt engineering expertise will also be well-received. The team is tasked with improving AI adoption in the CIB by providing prompt training.
For the VP and executive director roles, JPMorgan is paying AI enablement staff up to $200k in salary. The associate role pays up to $100k.
As of November, JPMorgan has rolled out its generative AI assistant, LLM Suite, to over 200k employees according to Business Insider. Chief data and analytics officer Teresa Heitsenrether says the next step for JPMorgan is rolling out agentic AI systems specific to JPMorgan's different teams.
JPMorgan CEO Jamie Dimon said at the Berenstein Strategic Decisions Conference last May that the bank had 400 use cases for AI, was aiming to reach around 800 use cases heading into 2025. Key areas of use for Dimon include "prospect, marketing, offers, travel, notetaking, idea generation, hedging, equity hedging and the equity trading floors." Hedge funds like Man Group are also building internal AI systems, with key areas of focus being the analysis of financial documents and code generation.
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