AI Prototyping & Transformation Associate

JPMorgan Chase & Co.•Columbus, OH

1d•Onsite

About The Position

Performance Consulting (PC) is JPMorganChase's internal management consulting practice — a strategy and transformation team that partners with the firm's businesses to solve their hardest operational and process challenges. Within PC, the Transformation Office is a rapid AI prototyping capability that moves engagements from recommendation to working solution. As a Process Improvement Associate within the Transformation Office, scoped to Process Intelligence (PI), you will be a hands-on contributor who learns the craft of AI-first prototyping by building alongside more senior team members. You assess processes, analyze data, and craft future designs to enhance operational performance, and you support the creation of working prototypes that demonstrate value through real execution, not slides. You are not a tool enthusiast looking for a place to use the latest model — you are a problem-solver developing the discipline to know when not to reach for them. Where the Senior Associate leads the build and owns the structured handoff, you contribute to the build under guidance, sharpen your technical credibility, and grow toward that standard. You bring energy, curiosity, and a bias toward action to a team that proves what's possible.

Requirements

Professional work or internship experience with a proven track record of developing strategic business recommendations or improvements that deliver measurable results
Demonstrated hands-on ability to build — you have written code, stood up applications or point solutions, or produced working outputs, even in an academic, internship, or early-career setting
Practical, developing experience using generative AI, copilots, or agentic tooling (e.g., Claude Code, Copilot) to produce real outputs — not just experiments
Proven ability to apply analytical and problem-solving skills to complex operational issues, with strong client management and communication skills
Demonstrated proficiency in data analytics, with experience interpreting models and diagrams to communicate data requirements and assets
Growing technical acumen — the ability to work credibly with engineers and reason about architecture, data, and integration at a foundational level
Business fluency — the ability to understand a business problem, frame it, and translate it into terms stakeholders at multiple levels can engage with
Strong communication and storytelling skills, making emerging concepts concrete for technical and non-technical audiences alike
A bias toward action, comfort with ambiguity, and the resourcefulness to bootstrap from incomplete information
Demonstrated foundational understanding of AI concepts, with the ability to identify processes and opportunities where AI solutions can drive operational improvement
Ability to travel up to 10%

Nice To Haves

2+ years of professional or internship experience within management consulting, financial services, and/ or professional process improvement background
Background in software engineering, product engineering, developer enablement, or a comparable technical discipline that supports hands-on credibility with delivery teams
Exposure to prompt design, workflow orchestration, human-in-the-loop controls, evaluation approaches, and responsible-AI guardrails
Technical skills in data analytics tools (e.g., SQL, Python, R) and visualization tools (e.g., Tableau, Power BI)
Exposure to regulated or large-scale enterprise environments where technology change must align with risk, control, and operational readiness requirements
Exposure to change management or human capital considerations in technology-driven transformation
Relevant certifications such as Lean Six Sigma (GB/BB), Google Data Analytics Certificate, or an AI/ML certification

Responsibilities

Support hands-on prototyping — contribute to apps, point solutions, and agentic workflows alongside the engagement team through rapid discovery, iterative build, and collaborative validation
Assess and map processes — assess processes, analyze data, and help craft future designs that enhance operational performance within PI engagements
Break down problems — use hypothesis-driven thinking and analysis to develop insights and actionable recommendations
Leverage AI tooling under guidance — use generative AI, copilots, and firm-approved platforms such as Claude Code and Copilot to produce real, working outputs, building fluency as you go
Capture institutional knowledge — help capture business rules and decision logic into durable assets that persist beyond the engagement
Learn to build AI-first — with support from senior team members, learn how to build and migrate toward AI-first solutions grounded in firm-prescribed facilities, controls, and guardrails
Craft compelling narratives — communicate complex ideas clearly to influence change within the organization
Account for adoption from the start — recognize that a prototype is only valuable if the organization can adopt it, and stay mindful of change management and human capital impact
Own your workstream deliverables — take ownership of assigned work from planning to execution, delivering high-quality outcomes within established timelines