Lead Software Engineer focused on building and scaling machine learning platforms and infrastructure at JPMorgan Chase. Responsibilities include designing, developing, and optimizing tools for the end-to-end ML lifecycle, integrating various ML capabilities, and ensuring platform reliability and security. Requires strong software engineering background, experience with ML platforms and MLOps, and Python proficiency.

Product Manager for an AI Platform at JPMorgan Chase, focusing on building and scaling a production entity data platform. The role involves owning the end-to-end product lifecycle for resolving millions of organizational records into a single, trusted global universe of entities and producing an arbitrated 'golden profile'. Responsibilities include developing product strategy, managing the product backlog, defining requirements for entity resolution and attribute arbitration, and leading delivery of entity resolution at scale using a balance of deterministic rules and ML-assisted matching. The role also involves introducing AI- and agent-assisted processing patterns and partnering with engineering, applied ML, and other stakeholders.

Lead Software Engineer focused on developing and deploying AI-powered solutions within the SAP Business Technology Platform (BTP) ecosystem. The role involves identifying AI use cases, building agentic AI capabilities, implementing solutions like RAG and intelligent document processing, and defining AI adoption frameworks, with a strong emphasis on SAP BTP services and MLOps practices.

Product Manager for AI and autonomous agents team focused on automating operations and workflows within Corporate and Investment Bank. Role involves setting strategy, leading researchers and engineers, and managing the product lifecycle for agentic AI pipelines.

Product Associate role focused on developing and deploying AI/ML models for authentication and identity verification within a financial institution. The role involves understanding user journeys, identifying opportunities for AI/ML solutions, and translating business requirements into technical solutions using advanced modeling techniques like transformers and graph neural networks. Collaboration with data scientists and engineers is key, as is ensuring model performance, scalability, and compliance.

Executive Director to lead a team of AI/ML specialists in developing horizontal capabilities (APIs, libraries) for AI hosting platforms within a large bank. The role involves hands-on experience in training and deploying models, leading teams, and ensuring responsible AI engineering practices.

Develops and implements LLM-based solutions, including RAG agents and agentic AI systems, with a focus on data analysis, model tuning, and evaluation metrics within a fintech domain.

Lead Software Engineer focused on building cloud platforms that integrate AI agents and LLM-powered tools to enhance developer productivity and automate platform operations. The role involves designing and developing secure, scalable cloud infrastructure, driving DevEx, and implementing AI/ML integrations.

Senior Lead Software Engineer focused on building, scaling, and maintaining robust machine learning platforms and infrastructure. The role involves designing and optimizing tools for the end-to-end ML lifecycle, including data engineering, feature management, model training, deployment, monitoring, and serving. Emphasis on secure, high-quality production code, MLOps practices, and collaboration with data scientists and ML engineers to accelerate ML development and operations within an enterprise environment.

Software Engineer III role focused on building agentic AI solutions within a large enterprise environment. Requires proficiency in Python/Java, system design, cloud technologies (AWS), and containerization. Familiarity with agent frameworks (LangGraph, Autogen), LLM evaluation tools, and model training/inference technologies is preferred.

Lead Software Engineer focused on building agentic AI systems, including multi-agent orchestration, tool-use chains, planning/reasoning loops, and memory architectures. Requires strong foundation in distributed systems, API design, microservices, event-driven architectures, and cloud platforms. Experience with LLMs, prompt engineering, fine-tuning, and evaluation is preferred.

Lead role in designing and delivering AI/ML solutions for data management and governance challenges within a large enterprise. Focuses on building prototypes, collaborating with business and engineering teams, and staying current with AI/ML research.

Lead Software Engineer role focused on integrating AI/ML techniques, including LLMs, Generative AI, NLP, RAG, and AI evals, into software systems. Requires experience with agentic workflows and frameworks, and managing/mentoring AI/ML teams. The role emphasizes hands-on delivery of production-grade solutions within a fintech domain.

This role focuses on evaluating and validating machine learning models, particularly in the context of fraud detection within a financial institution. It involves conducting independent tests, assessing risks, ensuring compliance with regulatory requirements, and mentoring junior team members. The core responsibility is to act as a quality gate for AI/ML models before they are deployed or used internally.

This role focuses on applying AI and data science, particularly LLMs, to enhance research methodologies and automate workflows within JPMorgan Chase's Global Research Center. The specialist will collaborate with analysts to identify opportunities for data-driven insights and workflow automation, ensuring data integrity and adhering to regulatory standards.

Lead Software Engineer, Vice President, to build a new AI-powered, promoter-based forecasting and planning platform for CIB Finance. The role involves hands-on engineering, architecture, and decision-making to deliver secure, resilient, and scalable software solutions. Responsibilities include designing and implementing LLM- and agent-based capabilities, building data/compute workflows on AWS and Databricks, and developing user-facing experiences with JavaScript/TypeScript and React. Requires strong experience in software engineering, cloud-native solutions on AWS, LLMs and agentic systems, Databricks, and modern web applications.

Senior Principal Cybersecurity Architect at JPMorgan Chase focusing on developing AI-enabled cybersecurity solutions, products, and models for the Consumer & Community Banking (CCB) line of business. The role involves advising on strategy, translating technical issues, driving adoption of new methods, creating reusable frameworks, and developing architectures for agentic systems, with a strong emphasis on cloud-native security, A2A security, and evaluating emerging technologies.

Software Engineer III role focused on designing, developing, and maintaining backend services for AI and Agentic AI applications using Python. The role involves building and integrating agentic frameworks (Langgraph, Langchain, Autogen, Google ADK) for autonomous marketing solutions, developing APIs for AI-driven workflows, and deploying applications on AWS.

Lead Software Engineer role focused on building AI-powered automation and IoT solutions, integrating LLM capabilities into business workflows and smart building systems. Requires strong full-stack development, system design, and experience with LLMs, generative AI use cases (RAG, agents, orchestration, evaluation/guardrails), and cloud-native microservices.

This role focuses on building and deploying predictive models and AI-enabled solutions, including LLMs, to drive business strategy and improve sales productivity within the JPMorgan Private Bank. The role involves end-to-end model lifecycle management, from data analysis and prototyping to production deployment and integration with business processes.

Lead the implementation of AI agents for campaign automation and optimization, and build foundational AI-ready data systems for marketing transformation in a financial services context.

This role provides second-line-of-defense (2LoD) independent oversight for JPMorgan Chase's Chief Data & Analytics Office (CDAO) Product and Platform organization, focusing on Data/AI platforms, model ingestion, agentic systems, and external AI services. The Director will develop and execute review strategies across the AI technical supply chain, ensuring compliance with risk appetite and regulatory expectations. Responsibilities include assessing risks in data flows, integrations, access controls, logging/traceability, and data residency, challenging remediation efforts, and overseeing governance for GenAI and agentic systems.

Product Director to lead AI Transformation in Payments, focusing on designing the future-state operating model, scaling AI capabilities, identifying client pain points, and driving adoption of AI-enabled workflows. This role requires strong change management, stakeholder alignment, and a practical understanding of GenAI/LLMs and the AI delivery lifecycle within a large enterprise and regulated environment.

Software Engineer III role focused on building AI agentic platforms and model serving infrastructure on AWS, integrating LLM APIs, and developing backend services using Python. The role involves working with various AWS services, implementing message queuing, and contributing to deployment pipelines.

JPMorgan Chase is seeking an Applied AI Machine Learning Vice President for their International Consumer Bank (ICB) Risk Modelling team in London. The role focuses on developing and managing machine learning models to mitigate identity verification fraud. Responsibilities include defining roadmaps, researching and adopting state-of-the-art and vendor models, ensuring model performance and governance, supporting synthetic data initiatives, and collaborating with various partner teams to meet regulatory requirements.

Applied AI ML Engineer Associate at JPMorgan Chase within the Consumer & Community Banking Machine Learning team. The role focuses on applying LLM-based methods, building and scaling software/ML platforms, and developing AI agents with tool integration and RAG solutions. Responsibilities include driving innovation, architecting ML models, ensuring scalability, and promoting quality and security in production environments.

Lead the development and deployment of machine learning solutions for a branch channel analytics team, focusing on a multi-action prioritization framework to optimize banker outreach. This role involves designing, developing, and deploying ML models, serving as a subject matter expert in ranking/recommendation systems and multi-objective optimization, and owning the full code development lifecycle.

Product Director leading the strategy, roadmap, and execution of AI-powered document solutions, leveraging technologies like OpenAI and AWS Bedrock, and focusing on agentic implementations. The role involves overseeing the product life cycle, managing stakeholders, and driving measurable business results within JPMorgan Chase's Consumer & Community Banking Operations Product organization.

Software Engineer III role focused on building and enhancing full-stack, cloud-native applications that integrate IoT data and LLM/generative AI capabilities for automation and workplace experiences. Responsibilities include software execution, production code, design artifacts, full-stack development, integrating AI/IoT features, data analysis, and troubleshooting. Requires strong system design, Java proficiency, experience with LLMs/generative AI productization, distributed systems, cloud platforms, microservices, and IoT architectures.

As a Principal Software Engineer at JPMorgan Chase, you will provide expertise and engineering excellence to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. You will execute creative software solutions, design, development, and technical troubleshooting for AI-enabled applications, create complex and scalable coding frameworks, and develop secure and high-quality production code. You will also advise cross-functional teams, serve as a subject matter expert, and contribute to the development of technical methods. The role requires formal training or certification on software engineering concepts, 7+ years of applied experience, DevOps experience, advanced Python skills, practical cloud-native experience, and experience in Computer Science or a related technical field. Experience with building AI platforms is highly preferred.

JPMorgan Chase is seeking an Applied AI ML-Vice President to join their Consumer & Community Banking Machine Learning team. This role focuses on applying LLM-based methods to enhance, build, and deliver trusted market-leading technology products. Responsibilities include applying technical judgment, evaluating performance, ensuring solutions are reliable, secure, and scalable, improving data quality, monitoring models in production, and iterating to reduce agent effort and improve operational workflows. The role requires experience in building and scaling software/ML platforms, ML frameworks, ML Ops, AI Agents, tool integration, and RAG-based solutions.

Product Director role focused on AI Orchestration within JPMorgan Chase's Marketing Product Portfolio. The role involves leading the strategy, requirements, and execution for transforming traditional business processes into agentic AI solutions, orchestrating end-to-end workflows. Responsibilities include driving use case definition, product roadmaps, collaborating with ML/AI teams, and influencing the AI technology stack.

This role focuses on developing and managing intraday liquidity analytics using AI/ML tools to forecast cash positions and manage limits within JPMorgan Chase's Corporate Treasury. The primary responsibility involves utilizing Python and ML to publish daily forecasts, derive insights from payments data, and maintain a back-testing framework for forecast accuracy. Experience with ML or time-series forecasting in financial workflows is required.

Lead Applied AI/ML role focused on building and productionizing LLM-based solutions for sales engagement optimization within a financial services context. Requires strong Python, NLP, and deep learning framework expertise, with experience in cloud deployment.

Seeking a Quantitative Research Associate to design, build, and deploy AI, LLM, and generative AI agent-based tools for credit portfolio management and trading. The role involves exploring ML techniques for market-making and optimization, leveraging data for opportunities, and automating reporting and hedging strategies. Requires advanced degree, 4+ years of quant experience in fixed income/credit, hands-on AI/ML/LLM application experience in financial markets, Python skills, and strong analytical abilities.

Executive Director to shape the enterprise AI data strategy, focusing on knowledge representation, ontologies, and data foundations for AI applications at scale within a financial services organization.

Senior Associate role focused on applied AI and quantitative modeling within the Consumer Business Modeling team at JPMorgan Chase. The role involves leveraging large consumer datasets to solve complex business problems using the full modeling lifecycle, from defining objectives to communicating results. Requires advanced degree in a quantitative field and experience in developing ML, optimization, or statistical models.

Lead the development and deployment of AI/ML models for financial services, focusing on customer needs in areas like credit card, home lending, and wealth management. This role involves end-to-end project leadership, stakeholder management, and ensuring regulatory compliance.

Lead Data Scientist at JPMorgan Chase within Cybersecurity and Technology Controls, responsible for developing and deploying Machine Learning solutions for security use cases like fraud and threat detection. The role involves data analysis, model development, feature engineering, model governance, and producing secure production code, with a focus on Generative AI, transformer architectures, and responsible AI practices.

Develops and deploys AI/ML models and generative AI solutions within web platforms and reporting tools for a financial services company, focusing on improving data delivery and user experience. The role involves mentoring other developers and integrating AI into existing analytics platforms.

Product Manager role focused on defining strategy and delivery for AI-driven products and autonomous agents, leveraging LLMs and agentic orchestration within a large financial institution. Responsibilities include identifying use cases, owning product strategy and roadmaps, leading cross-functional teams, and communicating with senior stakeholders to launch AI-enabled products end-to-end.

Software Engineer III - AI/ML Engineer at JPMorganChase within the AI For Technology group, responsible for delivering AI/ML projects through the ML development life cycle using Agile methodology. The role involves transforming business requirements into AI/ML specifications, designing and developing production AI/ML solutions, and creating secure, high-quality production code. Familiarity with agentic workflows and expertise in areas like LLMs, NLP, Knowledge Graph, Computer Vision, Speech Recognition, RL, Ranking/Recommendation, or Time Series Analysis is required.

Lead Software Engineer role focused on integrating AI/ML techniques, including LLMs and Generative AI, into production software systems within a financial services context. The role involves leading a team, architecting solutions, and developing secure, scalable AI-driven software.

Lead Software Engineer for AI/ML Data Platforms at JPMorgan Chase, focusing on building production-grade AI/ML applications and Generative AI agents. The role involves advancing experiments, developing scalable platforms, and ensuring operational stability, primarily serving AI Research and MLCoE teams within a fintech domain.

Senior Director of Software Engineering for AI Infrastructure Platform at JPMorgan Chase, leading multiple departments to deliver a unified AI infrastructure layer across on-premises, public cloud, and accelerated-compute vendors. Owns training and experimentation on a Kubernetes-standardized platform, acting as a design partner for architectural trade-offs and ensuring reliable, secure, and operable systems at enterprise scale. Responsibilities include standardizing AI developer workflows, building platform APIs, improving GPU availability and utilization, defining scheduling and placement strategies, embedding security and controls, driving operational excellence, and leading engineering teams.

The Quant Modeling Lead - Vice President role within JPMorgan Chase's Model Risk Governance and Review (MRGR) team focuses on the independent validation and risk governance of forecasting and scoring models, including those using advanced AI/ML techniques, for consumer banking applications. The role involves evaluating model conceptual soundness, performing independent testing, monitoring performance, and liaising with various internal and external stakeholders, including regulators.

Lead the design and delivery of AI/ML solutions for Market Operations at JPMorgan Chase. This role involves managing a team, partnering with business and technology stakeholders, and ensuring the successful implementation and scaling of AI-driven tools. The focus is on developing and deploying production-grade AI/ML applications, establishing best practices for evaluation and monitoring, and driving measurable impact.

ML Ops Engineer role focused on deploying, monitoring, and managing machine learning models in production environments within JPMorgan Chase's Cybersecurity team. Responsibilities include building CI/CD pipelines, optimizing infrastructure, and ensuring reliable and efficient AI system performance.