Senior Product Associate-AI Capabilities

JPMorgan Chase & Co.•Jersey City, NJ

3h•$99,750 - $150,000

About The Position

JPMorganChase Global Security is expanding its use of AI-enabled capabilities to strengthen security operations and risk management across the firm. In this role, you will support the Product Manager and work across functions to connect user needs, risk considerations, and technical constraints, translating strategic priorities into practical product delivery in a complex, regulated environment. You will help shape the playbook, not just inherit it. Beyond delivery, this role carries a responsibility to build the human foundation that makes AI successful. That means educating rather than just informing, partnering rather than just coordinating, and shaping how the organization thinks about AI with the same intentionality applied to the product roadmap. The ideal candidate is equally comfortable running a capability demo for a skeptical operations team as they are writing acceptance criteria with an engineering squad. They lead through credibility and conviction, able to bring along engineers, operators, and stakeholders who may not always share the same priorities or risk tolerance. We are looking for someone who sees AI not as a feature to ship, but as a capability to grow across the platform, the team, and the organization. That takes intellectual curiosity, a genuine comfort with iteration, and the ability to help others build confidence in rapidly evolving technology.

Requirements

3+ years of experience or equivalent expertise in product management or technical project delivery.
Hands-on experience with applied AI products, including GenAI, NLP, and automation.
Proficiency across the full product lifecycle, with hands-on experience in Agile/Scrum and SAFe, including backlog management, sprint planning, and working knowledge of Jira and Confluence.
Experience driving adoption through change management, enablement, and post-launch measurement.
Ability to translate complex technical concepts into clear, actionable requirements for non-technical stakeholders, including operations leaders and executive management, and to influence priorities across teams without direct authority.
Strong foundation in data analytics, with the ability to interpret and communicate data-driven insights.

Nice To Haves

Experience delivering AI products in complex, regulated environments, balancing risk, data governance, and audit needs with speed.
Experience supporting AI/ML-enabled products through deployment, production monitoring, and iterative improvement.
Knowledge of AI evaluation methods, prompt design, and responsible release practices.
Working knowledge of modern data platforms, APIs, and cloud environments such as Databricks, Snowflake, AWS, or Azure.
Proficiency in SQL and Python, with hands-on experience in BI and analytics tools such as Qlik, Tableau, Sigma, Power BI, ThoughtSpot, and Databricks, as well as workflow, case management, and automation platforms such as Pega, ServiceNow, UiPath, and Microsoft Power Automate.
Background in security, analytics, or data-intensive operational environments is a strong plus.
Bachelor's degree in computer science, data science, engineering, or equivalent practical experience - demonstrated delivery and domain impact are valued over a specific degree path.

Responsibilities

Support the Product Manager in taking AI capabilities from concept to production, which includes identifying new product opportunities through user research, discovery, journey mapping, market analysis, and ensuring roadmap recommendations reflect both customer needs and broader market trends.
Set delivery standards by translating platform initiatives into clear user stories (acceptance criteria, sequencing, dependencies) and supporting alignment with other Product Delivery Managers.
Support the delivery lifecycle with strong release discipline, ensuring responsible AI guardrails are in place, including data readiness, evaluation gates, deployment and rollback plans, production monitoring, and incident management.
Coordinate delivery of core platform artifacts (architecture, integrations, MLOps foundations, UX standards) with Technology teams.
Support release decisions through UAT, outcome verification, and defect triage, backed by clear metrics, thorough documentation, and regular stakeholder updates
Build AI literacy across Global Security through practical enablement (onboarding guides, explainer sessions, hands-on demos) that helps operations teams use and critically assess AI outputs.
Foster a culture of experimentation by encouraging iteration, sharing lessons learned, and creating space for teams to engage critically with new capabilities.