AI/LLM Product Manager - Senior Associate

Testing Site - JPMC; Palo Alto (CA); On-site; USD 120,000 - 170,000; Full time

Job summary

Testing Site - JPMC is seeking a Product Associate in Global Banking to help deliver a best-in-class enterprise Search capability, leveraging AI/LLM and modern SDLC practices. You will collaborate with data scientists, engineers, and designers to define features, ensure scalable, secure solutions, and align with regulatory requirements.

You will contribute to product vision, track KPIs, and drive data-driven improvements in search and AI initiatives within GB.

Qualifications

• 3-5+ years building and launching AI/LLM products.
• Strong collaboration with technology teams and stakeholders.
• Experience with AI/LLM data product lifecycle (discovery to monitoring).
• Familiarity with SFT, RLHF, RAG, and Agents.
• Knowledge of LLM frameworks and MLOps pipelines.

Responsibilities

• Define a clear product vision and strategy for Search and LLM initiatives within GB.
• Leverage technologies like Semantic Search, SFT, RLHF, RAG, and agents to enhance UX.
• Apply Boolean, Keyword, Faceted, and Full-Text Search techniques.
• Collaborate with business leaders, data scientists, engineers, and designers to gather requirements.
• Oversee integration and release of Search and LLM tech into GB products, ensuring scalability, security, and regulatory compliance.
• Define and track KPIs to measure success and drive data-driven improvements.

Skills

Collaboration

Product lifecycle

KPI tracking

SDLC

Stakeholder mgmt

Tools

ElasticSearch

LangChain

LangGraph

OpenLLM

AWS

MLOps

Job description

You enjoy contributing to the future of product innovation, supporting value creation for customers, assisting in successful launches, and meeting expectations. Join our dynamic team and make a meaningful impact by supporting the delivery of high-quality products that resonate with clients.

As a Product Associate in Global Banking (GB), you will assist in delivering a business-friendly, best-in-class enterprise Search capability incorporating the latest technologies (including AI/LLM) and applying best practices. You are expected to support the design and architecture of the solutions while focusing on various stages of the Software Development Lifecycle (SDLC).

Job Responsibilities

• Assist in developing and communicating a clear product vision and strategy for both conventional Search and Large Language Model (LLM)-based conversational User Interface (UI) initiatives within GB. Align product goals with business objectives and market needs.
• Leverage a wide range of cutting-edge technologies such as Semantic Search, Personalized Search, Supervised Fine-Tuning (SFT), Reinforcement Learning with Human Feedback (RLHF), Retrieval-Augmented Generation (RAG), and Agents to enhance user experiences.
• Incorporate established search methodologies and technologies, including Boolean Search, Keyword Search, Faceted Search, and Full-Text Search, to improve overall search capabilities and user experience.
• Collaborate with internal stakeholders, including business leaders, data scientists, engineers, and designers, to gather requirements, define product features, and ensure successful product delivery.
• Oversee the integration and release of Search and LLM technologies into GB products and services. Ensure that solutions are scalable, secure, and compliant with regulatory requirements.
• Help define and track key performance indicators (KPIs) to measure the success of Search and LLM products. Use data-driven insights to support informed decisions and drive continuous improvement.

Required Qualifications, Capabilities, and Skills

• 3-5+ years of building and launching AI / LLM products.
• Strong collaboration skills, with the ability to positively influence technology teams and stakeholders.
• Knowledge of AI/LLM and data product lifecycle, including discovery, data processing, model development, model deployment, and model monitoring.
• Familiarity with ElasticSearch, Supervised Fine-Tuning (SFT), Reinforcement Learning with Human Feedback (RLHF), RAG, and Agents.
• Knowledge of LLM frameworks such as LangChain, LangGraph, and OpenLLM.
• Understanding of operationalizing AI products responsibly through MLOps pipeline.
• Basic expertise in Cloud computing and architecture (e.g., AWS).

Preferred Qualifications, Capabilities, and Skills

• Search Product expeirence preferred, but nor required.
• Experience in Financial Services or other highly regulated industries.