JPMorgan Chase

This Director Researcher role focuses on building and deploying autonomous agentic AI solutions for a financial institution. The individual will architect and develop GenAI and Agentic solutions, deliver multiple collaborating agents to solve complex problems, and mentor a team of AI engineers. The role emphasizes bridging cutting-edge theory with enterprise-grade, large-scale, deployable systems, ensuring scalability, reliability, and security in production.

Lead the design and delivery of production-grade LLM systems for mission-critical financial products, focusing on scalable APIs, agentic workflows, and end-to-end ownership of LLM Suite products. This role bridges AI research with robust engineering for enterprise-wide AI adoption.

JPMorgan Chase is seeking an Applied AI ML Senior Associate to join their LLM Suite Engineering team in London. The role focuses on building secure, reliable, and production-ready AI/ML and agentic capabilities on the LLM Suite platform, leveraging public cloud (Azure, AWS) and modern agentic frameworks. Responsibilities include designing, developing, and troubleshooting software, writing high-quality code, and implementing GenAI services. The role emphasizes collaboration with senior engineers and operational stability.

Lead hands-on engineering for agentic and GenAI capabilities within the LLM Suite platform, focusing on designing, developing, and operationalizing production-grade AI/ML solutions using public cloud services and agentic frameworks.

Lead the deployment and scaling of advanced generative AI, agentic AI, and classical ML solutions within a financial services context. This role involves designing and developing multi-agent systems, enterprise-wide AI/ML frameworks, and production-ready code, with a focus on cloud migration optimization.

Lead the end-to-end delivery of advanced machine learning and AI solutions for Payments and Banking Operations, focusing on production deployment, scalability, and integration within a regulated fintech environment. This role involves developing innovative solutions including GenAI and agentic approaches, establishing MLOps practices, and providing technical leadership.

AI Engineering Director to lead a team developing horizontal LLM-based systems and agentic AI platforms for enterprise use cases. Responsibilities include designing and building production-grade AI systems, architecting retrieval patterns, engineering cloud-native platforms on AWS, optimizing AI systems, building APIs, and establishing evaluation/observability frameworks. Requires PhD or deep experience with LLMs/Agents, training/deploying models, and leading AI teams.

Director-level role focused on applying advanced ML techniques, particularly NLP, LLMs, and Graphs, to solve real-world problems within a regulated financial environment. The role involves developing state-of-the-art models, deploying solutions into production, driving firm-wide initiatives with large-scale frameworks, and researching new ML methods. Emphasis on agentic AI/multi-agent systems and LLM evaluation.

Lead Software Engineer for AI (VP) at JPMorgan Chase in Risk Technology, focusing on deploying and scaling generative AI and agentic AI solutions, particularly for natural language querying (NLQ) of data. The role involves designing reusable AI frameworks, developing multi-agent systems, guiding prompt engineering research, and building evaluation tools. Requires strong Python, system design, AWS, and LangGraph experience, with a focus on enterprise-scale solutions and data pipelines.

This role focuses on engineering and deploying LLM-based and generative AI applications within a financial institution. It involves developing, deploying, and ensuring the scalability and reliability of AI/ML solutions in production, with a strong emphasis on MLOps practices and utilizing vector databases and cloud platforms like AWS.

Lead the design, build, and deployment of end-to-end AI solutions, focusing on LLMs and agentic systems for business insights in a financial services context. This role involves advanced applied research, AI engineering, and data science expertise, with a strong emphasis on leading technical teams and driving complex initiatives.

JPMorgan Chase is seeking an Applied AI/ML Senior Associate Machine Learning Engineer to join their Commercial & Investment Bank team. The role involves combining AI techniques with financial data to optimize business decisions and automate processes. Responsibilities include building scalable data science capabilities, deploying ML services, researching datasets, communicating AI capabilities, documenting processes for regulatory compliance, and collaborating on production architectures. The position requires a Masters or PhD in a quantitative discipline, strong ML theory, NLP specialization, MLOps knowledge, PyTorch experience, and cloud provider familiarity. Experience with containerization and model monitoring is also expected.

Lead Applied AI/ML Engineer at JPMorgan Chase in London, focused on building and deploying AI-powered products for the Commercial & Investment Bank. The role involves leveraging NLP and Computer Vision to optimize business decisions and automate processes, requiring a blend of research and software engineering skills, with a focus on productionizing ML models and services.

Lead the design and delivery of human-in-the-loop (HITL) interfaces for supervising and steering AI agents in financial operations, focusing on production-grade web applications with React and TypeScript, and integrating with agentic workflows.

Lead a team of AI/ML scientists and engineers to design, develop, and deploy AI/ML solutions for market operations in a large financial institution. Focus on end-to-end delivery, production deployment, MLOps, and stakeholder engagement.

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.

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 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.

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.

JPMorgan Chase is seeking an Applied AI ML Director in London to lead a team of specialists in developing horizontal AI capabilities (APIs, libraries) for Corporate and Investment Banking. The role involves collaborating with Line of Business AI teams, mentoring engineers, and staying at the forefront of AI advancements, with a focus on domains like Documents, Email, and Speech. Requires a PhD or top commercial AI lab experience, hands-on model training/deployment, and experience leading AI teams.

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.

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.

Lead the design and implementation of advanced AI/ML models and tools for risk assessment and P&L prediction in treasury management within an investment bank. Drive strategic initiatives, own large-scale analytics projects, and automate reporting processes, partnering with technology and business stakeholders. Requires strong Python programming, software engineering, and quantitative finance skills.

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.

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.

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.

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.

Quantitative Trading & Research team at JPMorgan Chase seeks an Associate/Vice President to apply AI/ML techniques, including LLMs and sequential decision-making models, to transform business operations in Securities Services, Payments, and CIB Treasury. The role involves end-to-end project management, from data architecture to model development and stakeholder presentations, focusing on revenue growth and efficiency.

Lead Software Engineer focused on building and deploying AI/ML platform infrastructure on AWS for model deployment at scale within a financial institution. The role involves developing APIs for automated retraining, scheduling, endpoint deployments, and autoscaling, as well as implementing model monitoring solutions, with a specific emphasis on LLM monitoring and automated issue correction. The engineer will also engage with clients for support and contribute to disaster recovery and multi-region capabilities.

Software Engineer II - Applied AI at JPMorgan Chase in London. This role focuses on developing and deploying advanced machine learning models and generative AI applications/agents, with a strong emphasis on MLOps, AWS deployment, and integrating user feedback for self-improving systems. The role involves architecting AI solutions, analyzing data, ensuring scalability and reliability, and staying updated on AI advancements.

Senior Lead Software Engineer role focused on building and deploying ML solutions into production within an enterprise environment. The role involves creating cloud-based frameworks for hosting ML models, integrating AIML solutions, and ensuring production readiness. Requires strong Python and AWS skills, collaboration with Data Scientists, and experience with the full model development lifecycle.

Senior Lead Software Engineer with Python/Java expertise in a fintech environment, focusing on cloud-based systems and AI-driven solutions. The role involves developing production code, implementing RAG-based semantic search and LLM inference workflows, and serving as a subject matter expert in cloud deployment and AI technologies.

Lead Software Engineer focused on building AI-enabled features for Data Center Services, including anomaly detection, capacity planning, NLP, and knowledge retrieval. Requires strong full-stack experience with Angular and NodeJS, and understanding of AI/ML concepts.

Data Scientist Lead at JPMorgan Chase focusing on designing and implementing ML solutions using LLMs for ESG and Stewardship functions. The role involves content extraction, search, and principal-based reasoning, with a strong emphasis on building evaluation packages and production-quality code. Requires advanced Python, NLP, and LLM expertise, with preferred knowledge in financial markets and ESG.

Senior Associate role focused on applying and deploying ML solutions within JPMorgan's Commercial & Investment Bank, specifically in Payments Operations. The role involves researching, developing, and scaling ML capabilities, collaborating with engineering teams for deployment, and communicating results to stakeholders.

Lead Software Engineer with expertise in Python and AWS to engineer and deploy ML solutions into production, build cloud-based frameworks for hosting ML models, and integrate ML solutions into complex operational systems. Collaborates with Applied AI/ML group and Data Scientists.

Lead Software Engineer role focused on integrating AI/ML solutions within a financial institution. The role involves developing robust APIs, services, and libraries, architecting cloud infrastructure, and implementing MLOps best practices. Collaboration with Data Scientists and Line of Business teams is key, with a focus on deploying and scaling AI/ML capabilities.

Lead Software Engineer for an MLOps team in a financial institution, focusing on designing, building, and deploying scalable AI/ML solutions, including LLM-powered microservices and generative AI applications. The role involves end-to-end development, monitoring, and maintenance of AI/ML models and systems in a production environment.

Software Engineer III - AI - Chase UK role focused on building an advanced Agent Assist platform for contact centre agents. Responsibilities include designing, implementing, and deploying ML models, automating workflows, optimizing performance, and integrating AI solutions with enterprise platforms like Salesforce and AWS. The role involves a 30% innovation focus on researching and prototyping new features.