JPMorgan Chase is seeking an Experience Design Vice President to lead user experience research for their Connected Commerce division, focusing on travel. The role involves designing and executing research strategies using advanced quantitative and qualitative methods to understand customer needs and inform product enhancements. The candidate will collaborate with cross-disciplinary teams, translate insights into actionable recommendations, and promote a culture of continuous learning. A key aspect is demonstrating thought leadership in utilizing AI to improve research impact and efficiency.

This role focuses on designing and developing digital analytics requirements for UX/UI products, collaborating with cross-functional teams to deploy A/B tests and evaluate performance KPIs. The role involves developing dynamic dashboards, automating ETL processes, and performing data manipulation using SQL and Python. It also includes conducting statistical analysis and predictive modeling using machine learning methods, identifying personalization opportunities, and ensuring data integrity. The ideal candidate will have a Master's degree in a quantitative field, 3+ years of analytics experience, proficiency in SQL and Python with machine learning libraries, and experience with digital analytics and experimentation tools.

This role supports the development and deployment of machine learning models and tools for strategic decision-making within a financial organization. Responsibilities include data analysis, model testing, performance monitoring, and translating business needs into technical requirements. The role requires strong analytical and programming skills, particularly in SQL and Python, and experience in a financial institution.

This role focuses on optimizing fraud prevention strategies within a financial institution, leveraging AI/ML and graph analytics. The core responsibilities involve analyzing fraud drivers, developing strategic recommendations, monitoring and maintaining fraud authorization strategies, and leading roadmap initiatives. The role requires developing new model input variables and expanding data capabilities to improve authorization accuracy, while also ensuring compliance and collaborating with various internal teams.

This role focuses on designing and implementing secure solutions for software applications and platform products, with a specific emphasis on creating AI-enabled cybersecurity solutions and reusable frameworks. The responsibilities include architecting complex security frameworks, evolving security protocols, implementing IAM, and leading cybersecurity strategy for AI-enabled products. While AI/ML is mentioned as a practical cybersecurity discipline and the role involves creating AI-enabled solutions, the core function is cybersecurity architecture and engineering, not direct AI/ML model development or research.

This role focuses on integrating large language models (LLMs) into enterprise workflows, specifically within the Global Private Bank Tech Investments team at JPMorgan Chase. The Solutions Analyst II will bridge the gap between business stakeholders and developers, translating requirements into technical solutions. Key responsibilities include extracting insights from data, collaborating on architecture designs, managing project dependencies, and promoting continuous improvement. The role requires experience in solutions analysis, data fluency, and technical curiosity. Preferred qualifications include experience with LLM APIs, RAG patterns, prompt engineering, evaluation, risk controls, and LLM orchestration frameworks like LangChain.

The role involves quantitative research for portfolio analytics within Wealth Management. Responsibilities include developing and running risk and performance attribution models for multi-asset portfolios, building and maintaining models using Python and MATLAB, and applying statistical and machine learning techniques to investment research. The role also involves data management, model documentation, testing, and validation, as well as collaboration with portfolio managers and technology teams.

Software Engineer I role focused on developing tools for Model Risk Governance & Review (MRGR) at JPMorgan Chase. The role involves building applications primarily in Python, integrating LLMs to enhance automation, reporting, and decision-making, and supporting model reviewers and governance teams. Experience with full-stack development, Python, and integrating ML models is required.

Product Manager at JPMorgan Chase, focusing on Global IB Coverage & GCB. This VP-level role involves leading the end-to-end product life cycle, defining strategy and roadmap, gathering customer feedback, and collaborating with engineering, operations, and cross-functional teams (including compliance, legal, technology). The role emphasizes delivering high-quality, scalable, and resilient products, complying with regulations, and driving continuous improvement through data. While the role mentions embracing emerging technologies like AI to foster innovation, the core responsibilities are centered around traditional product management for banking products, not directly building or shipping AI models.

Product Associate role focused on using AI tooling, RAG, and LLMs to enhance core Product Management workflows like research synthesis, writing, analysis, and prototyping within employee platforms at JPMorgan Chase. The role involves collaborating with cross-functional teams, driving product discovery and delivery, and building foundational AI fluency.

This role focuses on delivering AI-enabled intelligent automation and workflow digitization within a fintech environment. The primary responsibility is to lead the end-to-end delivery of automation solutions, integrating tools like Tableau, Alteryx, UiPath, Power Apps, and Pega. The role involves understanding processes, designing solutions, ensuring quality and accuracy, and collaborating with stakeholders to optimize business functions. While AI tools are used, the core craft is not building AI models but rather implementing and managing automation solutions.

This role is responsible for overseeing operational risks related to third-party/outsourcing within a financial institution. A key aspect involves contributing to the development and implementation of AI-enhanced risk monitoring capabilities, specifically leveraging LLM-based functionalities to improve risk assessment and oversight. The role requires experience in financial services risk management, control assessments, and stakeholder influence, with a specific requirement for experience using AI models to drive value in risk management.

Principal Software Engineer at JPMorgan Chase focused on designing, developing, and maintaining complex, scalable Java frameworks using Spring Boot, with a significant emphasis on integrating AI solutions, including RAG and Applied AI, into enterprise systems. The role involves hands-on coding, architectural design, leading best practices, and providing technical thought leadership in AI.

The Data Product Management, Vice President role at JPMorgan Chase focuses on building and managing HR data products that support reporting, analytics, and AI/ML initiatives. The role involves defining strategy, roadmaps, and OKRs, partnering with various teams including AI/ML, and ensuring data governance, quality, and lifecycle management. While the role supports AI/ML, it is not directly building AI models but rather managing the data products that feed into them.

This role focuses on building and maintaining automated analytical workflows and tools for financial pricing operations, with an emphasis on evaluating and applying AI, generative AI, and intelligent automation to improve efficiency and decision-making. The role involves developing solutions using SAS, Alteryx, Python, and SQL, and supporting AI-assisted productivity use cases.

Product Manager for an AI-enabled Advisor platform at JPMorgan Chase, focusing on enhancing advisor workflows, client engagement, and service delivery. The role involves defining product strategy, roadmaps, and requirements for digital capabilities, with an emphasis on an AI-first approach to build a scalable and intelligent platform.

Product Manager for AI for Design within the Corporate & Investment Bank (CIB) Digital, Data & AI team. Responsible for the end-to-end product life cycle, from strategy and discovery to launch and client experience, focusing on building tooling to enable the design group and facilitate developer experience.

This role focuses on streamlining processes and improving data risk management within Business Banking. The Business Analyst will define business requirements, ensure adherence to policies, and implement initiatives to strengthen risk mitigation and data management controls. They will also partner with stakeholders to deliver analytics solutions and stay current on LLM-enabled capabilities.

Associate Quantitative Researcher role focused on delivering data-driven solutions for liquidity, funding, and capital management in financial markets. The role involves designing and implementing advanced models, developing predictive tools, and automating reporting processes using AI/ML applications. It requires strong quantitative, analytical, and programming skills, particularly in Python, with experience in large-scale systems and financial markets.

Product Manager role focused on AI controls and governance within a financial services company. The role involves managing AI control applications, reviewing AI use cases for risks, and contributing to the AI controls strategy. Requires experience in financial services, product management, and familiarity with AI governance frameworks.

This role involves applying AI and machine learning techniques to enhance investment research and portfolio management within a Wealth Management Chief Investment Officer team. The responsibilities include risk modeling, portfolio construction, and quantitative research using Python and large datasets, with a focus on equity markets.

This role focuses on technology risk and controls within an AI/ML Data Platform at JPMorgan Chase. The lead will identify, quantify, and mitigate technology risks, ensure control effectiveness, and provide subject matter expertise to stakeholders. The role requires experience in technology risk management, familiarity with risk frameworks and regulatory requirements, and a strong understanding of AI/ML technologies and associated risks.

Quant Analytics Senior Associate role at JPMorgan Chase focusing on marketing campaign management lifecycle for small businesses. Responsibilities include leading analytical financial optimization, building client relationships, leveraging analytics tools (including AI applications), collaborating with marketing teams, and coaching junior members. Requires a Master's or Bachelor's degree in a quantitative field with 7+ years of experience, proficiency in SQL, Python, SAS, R, Snowflake, and experience in financial analytics and marketing strategy.

Software Engineer III focused on developing and enhancing critical software applications, with responsibilities including building ML execution pipelines using PySpark, Databricks, Python, and Streamlit, as well as real-time model execution processes. The role involves system design, development, troubleshooting, and contributing to software engineering communities.

Lead Software Engineer for Salesforce at JPMorgan Chase, focusing on building and enhancing AI-driven solutions using Agentforce within the Consumer & Community Banking Technology Team. The role involves architecting scalable Salesforce solutions, developing Apex, LWC, and JavaScript, integrating with external systems, and providing technical guidance.

Senior Lead Software Engineer role at JPMorgan Chase, focusing on enhancing, building, and delivering technology products within Global Finance Technology. The role involves executing creative software solutions, leading engineering teams, developing secure production code, and identifying opportunities for automation and operational stability. It requires expertise in Java/Python, public cloud, CI/CD, and working knowledge of NoSQL and messaging technologies. While not directly building AI models, the role requires proficiency in AI/ML disciplines and exposure to building AI/ML driven applications, indicating an AI-adjacent function within a fintech domain.

This role focuses on delivering analytics solutions within a financial institution, specifically leveraging Snowflake's Cortex Analyst features to build and optimize text-to-SQL capabilities for business users. It involves designing, developing, and managing data structures, ensuring data quality, and driving research in predictive analytics and mobile capabilities, with a strong emphasis on natural language processing and AI-driven analytics.

Executive Director of UX Design for a Design System focused on Employee Experience at JPMorgan Chase. The role involves leading a team to define, govern, and evolve design patterns, components, and workflows to enable teams to deliver cohesive and personalized experiences. Key responsibilities include setting quality benchmarks, managing asset delivery, shaping product initiatives through system adoption, and collaborating with Product, Engineering, Content Design, Research, and Accessibility teams. The role also emphasizes leveraging AI technologies to improve team velocity and outcomes, and experience with agentic AI design systems is preferred.

Product Manager for AI-powered consumer experiences in the fintech domain, focusing on strategy, roadmap, and launch of AI features within a digital assistant product. The role emphasizes customer value, scalability, and cross-functional collaboration.

This role focuses on assessing technology and cyber operational risks within the Wealth Management line of business at JPMorgan Chase. It involves evaluating risks associated with modern software engineering, cloud, cybersecurity, and the adoption of AI-enabled tooling, coding assistants, and agentic AI capabilities. The officer will use Python and SQL for data analysis, identify root causes of production issues, and provide recommendations for improving operational resilience and risk management, with a particular emphasis on AI-related risks.

This role focuses on enabling AI adoption within a large financial institution by managing AI playbooks, curating AI component libraries, and supporting business users in integrating AI tools into their workflows. It involves operationalizing AI solutions, tracking adoption metrics, and synthesizing progress for senior management.

Control Manager (VP) at JPMorgan Chase responsible for leading and building an enhanced control framework for AI-accelerated Continuous Delivery (CD) Product Delivery. The role involves risk assessment, continuous improvement, and ensuring compliance in an AI-driven environment, with a focus on the Card Marketing space, specifically Rewards and Benefits Loyalty teams.

This role focuses on designing the user experience for AI-driven products and services within financial services, specifically for marketing. The designer will collaborate with engineering and AI teams to create and validate conversational flows and agentic systems, ensuring inclusive and accessible design. While the role involves working with LLM-powered systems and agentic AI, the core function is product design and user experience, not direct AI model development or research.

Senior Product Designer (VP) to drive the evolution of advisor-facing digital experiences within the Private Bank, with a core focus on alternative investment and wealth management products. This role will redefine the alternative investments experience, building seamless, user-centric experiences that enable advisors to navigate complex product structures. The designer will combine strong hands-on craft with the ability to influence product direction, align senior stakeholders, and raise design quality across squads.

Seeking an AWS Data Engineer with expertise in AI, Python, Spark, and AI productivity tools to design, build, and optimize scalable data pipelines and architectures on AWS, leveraging Data Lake, Snowflake, and distributed processing technologies. The role involves collaborating with data scientists and analysts to deliver AI-driven data solutions and using AI assistants to enhance productivity and code quality.

Senior Principal Software Engineer role at JPMorgan Chase focusing on leading the strategy and development of customer platform technologies, creating novel code solutions, and driving the adoption of technical methods. The role requires deep expertise in building and operating high-throughput data platforms and experience applying AI/ML to enhance engineering outcomes and platform intelligence within a secure, stable, and scalable environment.

Senior Director of Product for an API Management Platform at JPMorgan Chase. The role focuses on leading the product strategy, development, and innovation of a large-scale, mission-critical platform that serves both internal and external developers. A key aspect of the role involves leveraging AI technologies, particularly RAG, to enhance developer experience and platform capabilities, ensuring scalability, reliability, and security.

Site Reliability Engineer III role focused on supporting AI/ML platforms and products within a financial institution. Responsibilities include ensuring reliability, capacity planning, and incident response for AI/ML infrastructure components like Databricks, Vector Databases, and Model Serving endpoints. The role also leverages Agentic AI concepts (AI Agents, RAG, automation frameworks) for SRE functions such as intelligent incident triage and self-healing workflows.

This role is for a Test Manager at JPMorgan Chase focused on transforming testing practices within Securities Services using automation, AI, and advanced analytics. The primary focus is on improving efficiency, coverage, and quality of testing through strategic initiatives, process standardization, and adoption of new technologies. While AI is mentioned as a tool to enhance testing, the core function is not building AI models but rather applying AI tools and driving transformation in a financial services context.

Lead Data Scientist at JPMorgan Chase focused on marketing analytics, leveraging modern data science and AI tools to improve measurement and streamline processes. Requires strong analytical, communication, and project management skills.

This role is responsible for building and operating an Enterprise Feedback Operating System that consolidates employee feedback from various sources into actionable insights for product decisions. The role involves synthesizing data using AI/ML techniques like sentiment analysis and auto-categorization, creating insights dashboards, and partnering with product teams to translate insights into roadmap items. While AI/ML techniques are used for analysis, the core deliverable is the feedback system and insights, not the AI models themselves.

Product Manager for SaaS Data Infrastructure Team, responsible for launching Data/AIML products across JPMC. Focuses on end-to-end product lifecycle, customer voice, and collaboration with engineering and data science teams. Requires familiarity with big data technologies, GenAI use cases, and cloud platforms like AWS and Snowflake.

Quantitative researcher for an equity derivatives flow desk, focusing on advanced analytics, optimization, and modeling for volatility trading. Responsibilities include developing pricing and risk models, client analytics, and hedging optimization tools, leveraging machine learning and data-driven techniques.

Product Manager role focused on customer insights within Payments Data & Analytics at JPMorgan Chase. The role involves end-to-end product lifecycle management, developing strategy, managing backlogs, defining KPIs, and collaborating with cross-functional teams. A key aspect is driving the adoption of AI-powered features and products, translating AI/ML concepts into product capabilities, and creating new revenue streams. Experience with AI/ML concepts and creating AI solutions is required.

Quant Analytics Associate Senior role at JPMorgan Chase within the Consumer and Community Banking division, focusing on Collections and Recovery Operations. The role leverages data governance, predictive analytics, data science, and machine learning to understand and predict customer behavior, optimize performance, and manage operational expenses. Responsibilities include data programming, trend monitoring, applying AI technology for efficiency, and collaborating across functions to implement strategies and mitigate risks. Requires intermediate to advanced knowledge in statistics, predictive modeling, and machine learning, with proficiency in SQL, SAS, R, Python, and visualization tools.

This role is for an AI Compliance, Conduct and Operational Risk (CCOR) Vice President within JPMorgan Chase's Data & AI CCOR team. The primary focus is on providing independent second-line coverage for the Central Data & Analytics Office's (CDAO) AI initiatives, ensuring appropriate governance and controls for safe scaling and adoption of AI across the firm. Responsibilities include assisting in aligning policies, guidance, training, and testing for AI, addressing operational, compliance, and conduct risks, and supporting engagement with regulatory bodies like the EU AI Act. The role requires expertise in AI risk management, governance, and collaboration with various stakeholders to ensure compliance and manage risks associated with AI-enabled platforms and products.

Lead Software Engineer focused on full-stack development, including integrating AI/ML models into enterprise applications within the fintech domain. The role involves designing, developing, and troubleshooting software solutions, with a strong emphasis on microservices, cloud technologies, and CI/CD practices. While the role requires hands-on experience with AI/ML models and frameworks, its primary output is the shipped product (L6), not the AI models themselves.

Lead Software Engineer for a cloud-based payments platform, focusing on high performance and low latency. The role involves building new payment flows end-to-end, leveraging AI extensively for development processes, and contributing to innovation and operational stability in a rapidly expanding business.