JPMorgan Chase

Lead Applied AI/ML Scientist role focused on developing and deploying agentic systems using LLMs and other AI solutions for payment processes, fraud detection, and customer experience enhancement within a financial services context. Requires strong Python, ML/DL framework, and agentic system tooling experience, with a focus on scalability, regulatory compliance, and translating model outcomes into business impact.

Product Manager (VP level) for Conversational AI within JPMorgan Chase's Machine Learning and Optimization team. The role involves defining AI/ML/NLP product strategy, leading projects from concept to delivery, and incorporating advancements in Gen AI, agentic systems, LLMs, and deep learning. Responsibilities include creating and tracking conversational AI metrics, collaborating with data annotation teams for training and evaluation data, managing the product backlog, and leading agile scrum teams. Requires expert-level NLP/ML experience, particularly in deep learning, LLMs, and agentic systems, with a proven ability to build large-scale AI systems and lead cross-functional teams.

Vice President role in AI for Operations at JPMorgan Chase, focusing on designing, building, and scaling NLP solutions for customer and internal agent experiences. The role involves applying LLM-based methods, evaluating performance, and ensuring solutions are reliable, secure, and scalable. Responsibilities include full product development lifecycle, advanced analytics, and contributing to continuous learning.

Develop and implement GenAI and Agentic AI solutions using Python to enhance automation and decision-making processes within a Private Bank setting. This role involves analyzing existing processes, designing autonomous AI agents, applying LLMs and ML techniques, and collaborating with stakeholders to solve complex business challenges through cloud-centric software delivery.

As an Applied AI/ML Senior Associate in the AI for Operations organization at JPMorgan Chase, this role focuses on designing, building, and scaling cutting-edge Natural Language Processing (NLP) solutions to improve customer and internal agent experiences within the Consumer & Community Banking division. The role involves applying LLM-based methods and advanced analytics to solve complex business problems, working across the full model lifecycle from defining objectives to production deployment, and contributing to operational workflows through intelligent search, summarization, classification, and next-best-action recommendations.

This role focuses on designing, building, and productionizing Generative AI and Agentic AI solutions, including LLM/SLM-powered applications like RAG, summarization, chat experiences, and tool-using agents. It requires strong software engineering skills in Java/Python, API development, MLOps, and cloud deployment on AWS, with an emphasis on secure coding, reliability, and automated evaluation.

Associate Senior Data Scientist at JPMorgan Chase in Bengaluru, focusing on designing, deploying, and managing prompt-based LLM models for NLP tasks in financial services. The role involves prompt engineering, LLM orchestration, building data pipelines, and developing tools for model training and evaluation, with a requirement for Python, PyTorch/TensorFlow, cloud platforms, and MLOps.

Vice President in the CIB Technology team at JPMorgan Chase, focusing on analyzing business problems, experimenting with state-of-the-art models, and developing machine learning and deep learning solutions. The role involves leading AI/ML initiatives, defining roadmaps, developing models for NLP, personalization, and recommendation systems, and operationalizing end-to-end ML pipelines for use cases like Document Q&A, Search, and Information Retrieval. It also includes building batch and real-time prediction pipelines, collaborating with various teams for production deployment, and working with LLMs and Gen AI solutions.

Lead the design, development, and deployment of advanced AI, GenAI, and large language model solutions, acting as a subject matter expert and collaborating with cross-functional teams to deliver scalable, production-ready AI systems. This role involves end-to-end Python development, integrating generative AI, driving adoption of ML infrastructure, optimizing performance, and ensuring responsible AI practices and governance within a fintech domain.

Principal AI/ML Engineer at JPMorgan Chase focused on building and operating LLM-powered APIs and agentic AI systems. The role involves designing agent architectures, writing production code, creating reusable components, managing the end-to-end ML lifecycle, optimizing inference, and embedding responsible AI practices. Requires strong Python, LLM/agentic AI experience, MLOps, and cloud deployment skills.

Director-level role focused on defining and implementing governance frameworks for agentic AI within a financial services context. The role involves establishing risk management, oversight, and best practices for multi-agent systems and autonomous AI, aiming to accelerate safe AI deployment and position the company as an industry leader. Requires deep technical understanding of AI/ML, agentic systems, and regulatory landscapes.

Lead Software Engineer focused on AI/ML and Infrastructure as Code (IaC) within a financial services technology team. The role involves designing, developing, and deploying AI/ML models and agent-based systems for automation, including IaC development, CI/CD enhancement, and AI-powered observability. Requires strong experience in AI/ML engineering, agent-based systems, IaC automation, observability tools, and programming languages like Python or Java.

Lead AI/ML Engineer (VP level) at JPMorgan Chase, focusing on designing and delivering enterprise-scale AI/ML solutions, particularly LLM-based systems and agent workflows. The role involves hands-on coding, setting engineering standards, defining architectural patterns, and ensuring production readiness with strong observability and operational rigor. It emphasizes building Copilot-integrated solutions and managing the AI/ML lifecycle.

Lead engineer to build and deploy generative AI, agentic AI, and LLM solutions, focusing on context engineering, semantic modeling, and unified semantic layers within a regulated financial services environment. This role involves end-to-end development from proof-of-concept to production, including data pipelines, model training, evaluation, and responsible AI practices.

JPMorgan Chase is seeking a Quant Modeling Senior Associate with 5+ years of experience in data science, machine learning, or AI to join their Investment Risk & Analytics team. The role involves designing, developing, and deploying advanced AI/ML models, including generative AI and deep learning, for risk quantification and strategic decision-making. Responsibilities include the full AI/ML lifecycle, risk modeling, scenario analysis, and mentoring junior staff. Requires a strong background in statistics, mathematics, and programming in Python, with experience in investment products and data visualization.

This VP AI/ML Data Scientist role focuses on translating complex banking challenges into production-grade AI/ML and LLM solutions, including building intelligent agents and LLM-based systems for various banking use cases. The role involves end-to-end pipeline ownership, MLOps implementation, and ensuring governance and compliance in a regulated environment.

Lead an applied AI/ML team within a financial services context, focusing on developing and productionizing scalable, trustworthy, and explainable solutions. Responsibilities include defining technical vision, managing ML workflows, and applying expertise in areas like LLMs, NLP, RL, and advanced ML techniques including inference, fine-tuning, RAG, and prompt engineering. The role requires hands-on experience and leadership in building and operating AI/ML solutions.

Software Engineer III - Applied AI at JPMorgan Chase, focused on developing and deploying generative AI applications and agents, with expertise in MLOps, AWS, and integrating user feedback for self-improving systems within the fintech domain.

Lead Software Engineer for JPMorgan Chase's Consumer & Community Banking division, focusing on designing and building critical technology solutions for Chase AI components like Chase Agent, Agent Operating Memory, Domain Agents, Agentic Experience Service, and Assurance. The role involves creating secure, high-quality production code, executing software solutions, producing architecture and design artifacts, and troubleshooting complex problems. Key responsibilities include adopting new technologies for agentic solutions, collaborating with cross-functional teams, leading code reviews, mentoring junior engineers, and ensuring compliance with security, privacy, and regulatory requirements. Requires hands-on experience building agentic systems using LLMs/SLMs, proficiency in Java/Python, experience with Spring AI or Python frameworks, AWS, and understanding of LLM patterns like function calling, RAG, and safety guardrails.

Lead Data Scientist role focused on applying NLP and LLM expertise to develop business-centric AI solutions for investment processes, client experiences, and operations within JPMorgan Asset Management. The role involves extracting insights from financial data, building AI solutions for content extraction, search, Q&A, reasoning, and recommendation, and collaborating with engineering for scalable delivery.

Principal Architect role focused on designing and delivering production-grade Generative AI and LLM systems, including agentic workflows, for financial services. Requires strong software engineering and ML engineering experience with cloud platforms and various programming languages and frameworks.

Product Director for AI/LLM initiatives, focusing on enterprise Search capabilities. The role involves overseeing the product roadmap, development, and execution of generative search solutions using technologies like RAG, Agents, SFT, and RLHF. Requires experience in the AI/LLM product lifecycle and operationalizing AI responsibly.

Lead Engineer for Agentic Generative AI and Natural Language Querying solutions within Risk Technology at JPMorgan Chase. Focuses on designing, deploying, and scaling multi-agent systems, AI frameworks, and data pipelines for querying structured and unstructured data via natural language. Requires strong Python, system design, and AWS experience, with specific mention of LangGraph for orchestration.

Associate Data Scientist focused on NLP/LLM applications within Asset Management, responsible for developing and deploying agentic frameworks, applying ML techniques to improve decision-making, and collaborating with stakeholders to reengineer processes and enhance client experiences.

Lead engineer for an enterprise-scale generative AI and agentic AI initiative focused on natural language querying of structured and unstructured data. The role involves designing and deploying multi-agent systems, NLQ frameworks, and data pipelines, with a strong emphasis on production code quality and AWS infrastructure.

Quantitative Analyst with a focus on AI/ML/LLMs for investment research, alpha generation, portfolio optimization, and risk management in financial markets. Responsibilities include researching and implementing quantitative models, applying NLP to textual data, identifying alpha signals, and collaborating with teams to implement models in production. Requires a quantitative Master's/PhD, 3+ years of experience, expertise in ML/DL/AI/LLMs/NLP, strong coding skills (Python), and knowledge of financial markets. Regulatory licenses are required.

Senior Associate role focused on building and scaling production LLM agents for finance workflows, involving RAG, tool use, multi-step reasoning, evaluation frameworks, guardrails, and MLOps practices on cloud platforms.

Senior Lead Software Engineer focused on architecting, building, and scaling autonomous AI agent systems. Requires deep experience in agentic AI, LLMs, Python frameworks (LangChain, etc.), cloud platforms, and vector databases. The role involves technical leadership and driving the delivery of production-grade AI agent systems.

JPMorgan Chase is seeking a Vice President for their Applied Artificial Intelligence & Machine Learning team in Mumbai. This role focuses on developing and deploying scalable ML solutions for KYC and operations, with potential for commercialization. The position requires a Master's or PhD in a quantitative field, strong Python skills, and experience deploying ML models in production at scale. Experience with NLP, LLMs, and Agentic AI systems is preferred.

This role focuses on applying AI/ML and GenAI solutions within the Home Lending sector of JPMorgan Chase. The Lead will design, develop, and deploy AI/ML/GenAI solutions, including LLMs, RAG, NLP, and AI Agents, and build MLOps/LLMOps pipelines on cloud platforms. The role requires extensive experience in applied AI/ML engineering, production deployment, and proficiency with ML frameworks and cloud technologies.

This role focuses on designing, developing, and deploying advanced AI/ML models for investment risk and analytics within a fintech domain. It involves the full lifecycle of AI/ML initiatives, from data engineering and model development to deployment and monitoring, with an emphasis on generative AI, deep learning, and reinforcement learning. The role also requires risk modeling, scenario analysis, and collaboration with technology and business stakeholders, including participation in governance and regulatory forums.

JPMorgan Chase is seeking a Quant Modeling Associate with 3+ years of experience in AI/ML to design, develop, and deploy advanced AI/ML models for investment risk oversight. The role involves the full lifecycle of AI/ML initiatives, including data engineering, model development, validation, deployment, and monitoring, with a focus on generative AI and deep learning techniques. The associate will collaborate with technology teams, present findings, and stay updated on AI trends, while also participating in governance and regulatory discussions.

Lead the development and implementation of GenAI and Agentic AI solutions using Python to enhance automation and decision-making processes within JPMorgan Chase's Private Bank. This role involves designing, deploying, and managing prompt-based models on LLMs, conducting research on prompt engineering, and building data pipelines and evaluation frameworks for these models on cloud platforms.

JPMorgan Chase's Commercial and Investment Bank Chief Analytics Office is seeking an Embedded AI Senior Associate to accelerate high-impact AI programs, focusing on generative AI, LLMs, and Agentic AI. The role involves close collaboration with business experts and analytics/technology teams for end-to-end delivery of AI solutions, ensuring responsible AI use and staying updated with cutting-edge research. Responsibilities include identifying AI solutions, analyzing data, communicating insights to senior stakeholders, and delivering AI solutions.

The role focuses on developing and deploying modular components for agentic systems, enabling intelligent automation and orchestration within business platforms. It involves integrating these capabilities into existing systems, containerizing and deploying them on cloud platforms, and applying advancements in agentic frameworks, LLMs, and GenAI. The role also includes leading a team of senior resources focused on agentic solutions and infrastructure development.

Develops and maintains modular components for agentic systems, integrating AI/ML initiatives, containerizing and deploying on cloud platforms, and leveraging agentic frameworks, LLMs, and GenAI. Requires hands-on experience with agentic systems in production and strong Python skills.

Lead Engineer role focused on designing, building, and productionizing autonomous and assistive AI agents and multi-agent systems. This involves implementing RAG, integrating tools, prompt engineering, guardrails, and orchestrating workflows, with a strong emphasis on scaling and reliability within a fintech domain.

Senior Associate Applied AI Engineer focused on building and deploying agentic AI systems, including multi-agent architectures, RAG pipelines, and tool integration, within a financial services context. The role involves productionizing autonomous agents, orchestrating complex workflows, and ensuring safety through prompt engineering and guardrails.

Associate Applied AI & ML Scientist role at JPMorgan Chase focused on developing and deploying AI/ML solutions for Market Operations. Responsibilities include building ML models, deploying solutions for automation and anomaly detection, architecting generative AI applications, and maintaining production-grade tools. Requires experience with Python, ML libraries, MLOps, LLMOps, and cloud platforms.

JPMorgan Chase is seeking an Applied AI ML Researcher Senior Associate to build next-generation autonomous agents for the financial industry. This role focuses on developing GenAI and Agentic solutions to automate complex operational processes, deliver collaborative agents that orchestrate workflows, and contribute to the production deployment of AI/ML solutions.

AI Engineer role at JPMorgan Chase focusing on the research, deployment, and optimization of large models, including training, fine-tuning, and prompt engineering. The role involves implementing AI tools in enterprise business scenarios, developing AI platforms, and building AI workflows and agents. Requires strong algorithm and engineering capabilities with experience in RAG, Agent, LangChain, and large model training frameworks.

Lead role focused on designing, deploying, and managing prompt-based LLM models for NLP tasks in financial services. Involves research into prompt engineering, LLM orchestration, agentic AI, building data pipelines, and developing tools for model training, evaluation, and optimization. Requires strong Python, PyTorch/TensorFlow, cloud platform, and MLOps experience.

This role focuses on applying GenAI, ML, and statistical models, with a strong emphasis on causal inference, to solve business problems in the Global Wealth Management space. The goal is to build next-generation decision systems for pricing, campaign targeting, and understanding cause-and-effect relationships in observational data.

Software Engineer III role focused on designing and delivering AI-powered solutions on SAP BTP, building agentic AI capabilities, and leading proof-of-concept initiatives. Requires experience in AI/ML solution development, SAP BTP, Python/JavaScript, and MLOps practices.

Lead Data Scientist to monitor AI-relevant trends and develop local economic intelligence using LLM models and GenAI tools. Responsibilities include data curation, analytics, modeling, insight generation, and building data pipelines, with a focus on AI disruption monitoring and local economic impact.

Senior Lead Architect role focused on AI strategy, governance, and architecture for AI/ML solutions in financial services, including agentic systems, RAG, and hybrid LLM/SLM models.

Lead Software Engineer focused on building and deploying enterprise-grade AI solutions, including RAG pipelines and agentic AI systems, with a strong emphasis on production-level concerns like scalability, cost, latency, privacy, hallucination mitigation, and observability. The role requires fluency with AI-assisted development tools and hands-on experience in building AI/ML features in production environments.

Quantitative trading role focused on building systematic trading strategies using AI/ML techniques for pricing, risk management, and execution in Rates markets. Involves analyzing large datasets, back testing strategies, expanding modeling tools, and maintaining trading software systems.