Senior Lead Software Engineer to design, develop, and deploy client-facing Generative AI and Agentic AI solutions for a Private Bank. This role involves architecting prompt-based LLM models, building autonomous agentic AI workflows with multi-step reasoning and tool use, integrating with external data sources, and developing scalable data pipelines and APIs. The position requires strong programming skills in Python or Java, experience with cloud platforms, and a deep understanding of security and regulatory compliance in financial services.

This role focuses on architecting and scaling production-grade LLM systems, including APIs and agentic workflows, for enterprise-wide adoption in a financial technology setting. It emphasizes end-to-end delivery, performance, and continuous improvement, bridging AI research with robust engineering for real business impact.

This role focuses on the end-to-end lifecycle of LLM-based agents, from research to production deployment. The engineer will define research directions in areas like multi-step planning, tool use, and safety, build production systems that meet strict constraints, and partner with other teams to bring these systems to market. The role emphasizes building AI that is auditable, explainable, and safe within a regulated financial domain, with a focus on customer-facing financial tasks.

Lead the research and end-to-end lifecycle of LLM-based agents for financial tasks, focusing on multi-step planning, tool use, safety, and production deployment under strict regulatory constraints. This role involves fine-tuning, optimizing LLMs, applying reinforcement learning, scaling systems, and implementing robust safety and compliance controls.

JPMorgan Chase is seeking a Vice President to lead the design, deployment, and scaling of LLM agents and AI-driven solutions for finance workflows. The role involves architecting and building multi-agent systems using techniques like LangGraph, RAG, and tool use, integrating them with various data sources and APIs, and driving research in Gen AI and autonomous workflows. The candidate will also mentor teams and communicate technical concepts to stakeholders.

AI/ML Director to lead the enterprise portfolio for agentic AI, automating complex business workflows at scale. Responsibilities include architecting, developing, and productionizing autonomous and assistive AI agents, designing multi-agent systems using frameworks like LangChain and CrewAI, implementing RAG pipelines, building agent tools, and deploying scalable AI services with robust evaluation and governance.

Lead the development and deployment of production-grade advanced ML solutions, focusing on Generative AI capabilities including LLM-powered systems like RAG and agentic AI. The role involves fine-tuning, evaluation, and operating models reliably in production within a regulated fintech environment.

Lead Researcher role focused on architecting and developing GenAI and agentic solutions for complex operational processes within a financial institution. The role involves delivering collaborating agents, orchestrating workflows, building reusable services, and mentoring a team, with a strong emphasis on production deployment and scalability.

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.

Executive Director Data Scientist role focused on leading the strategy, delivery, and adoption of applied AI/ML solutions within JPMorgan Chase's Asset and Wealth Management team. The role involves hands-on ML engineering, MLOps, GenAI/LLMs, and team leadership to drive measurable business outcomes in financial services.

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

This role focuses on designing, building, and deploying AI and LLM-based solutions to transform model risk management processes within JPMorgan Chase's AI Center of Excellence. The associate will conduct independent model validation and governance, with a focus on AI/ML, LLM, and Generative AI systems, and enable other teams to leverage AI tools effectively.

Lead Data Scientist for JPMorgan Chase's Finance Technology team, focusing on building and deploying production-grade AI/ML solutions, including LLMs, Gen AI, and agentic workflows, for finance processes. The role involves managing a global team and collaborating with business and technology partners.

Lead Applied AI/ML role focused on delivering end-to-end ML capabilities for payments, including fraud detection, operational automation, and client experience. Responsibilities include designing, building, and deploying production-grade ML systems, defining evaluation metrics, establishing model lifecycle standards, and partnering with risk/compliance teams. Requires strong hands-on expertise in neural networks, Transformers, fine-tuning, distillation, and software engineering skills in Python with PyTorch/TensorFlow.

Associate Client Advanced Analytics role at JPMorgan Chase focused on building ML models for segmentation and prediction, and delivering GenAI solutions to boost advisor and marketer productivity and personalization. The role involves stakeholder engagement, analyzing client behavior, developing data models, and implementing various ML techniques within AWS environments and LLM APIs.

AI Research Lead focusing on Natural Language Processing within the financial services domain, developing novel techniques and state-of-the-art ML models for commercial applications.

AI Research Scientist role at JPMorgan Chase focused on developing novel techniques, tools, and frameworks for large-scale problems in financial services. The role involves formulating problems, developing algorithms and models, conducting experiments, and contributing to business applications, open-source software, and patents.

AI Research Scientist role at JPMorgan Chase focused on developing novel techniques, tools, and frameworks for large-scale problems in financial services. The role involves formulating problems, developing algorithms and models, conducting experiments, and contributing to business applications, open-source software, and patents.

Machine Learning Scientist - NLP - VP role focused on developing and deploying Generative AI solutions within JPMorgan Chase's Machine Learning Center of Excellence. The role involves research, thought partnership, cross-functional collaboration, and leading firm-wide initiatives to apply ML models across the business. Requires a PhD or MS with experience in GenAI, ML/DL toolkits, experimental design, and communication skills.

Machine Learning Scientist specializing in NLP and Generative AI (GenAI) to develop and deploy state-of-the-art models for complex business challenges within JPMorgan Chase. The role involves research, thought partnership with leaders, cross-functional collaboration for production deployment, and leading firm-wide initiatives with large-scale frameworks. Requires a PhD or MS with experience in GenAI, ML/DL toolkits, experiment design, and communication skills.

Machine Learning Scientist (VP) in the Machine Learning Center of Excellence at JPMorgan Chase, focusing on NLP and Generative AI. The role involves owning the full lifecycle of ML solutions, from research and development to production deployment, acting as a thought leader, and driving cross-functional collaboration to implement new ML methods and large-scale frameworks for business impact within the financial services industry.

JPMorgan Chase is seeking an Executive Director for their GenAI Engineering team, focusing on building AI applications and platforms in financial services. The role involves hands-on development, ML/LLM model creation, and production deployment on cloud platforms, requiring strong leadership and technical expertise in AI solutions.

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 Software Engineer for a Data Products Framework platform that uses AI/Agentic AI to enable users to discover, design, build, and productionize governed data products at enterprise scale on AWS. The role involves leading a team, setting technical vision, and architecting AI/Agentic AI layers including intent agents, NLP Text-to-SQL, Knowledge Graphs, RAG, Vector Databases, and Agent-to-Agent communication.

Lead the design and delivery of LLM-powered solutions for commercial banking use cases like content extraction, enterprise search, reasoning, summarization, and recommendations. Partner with engineering and product teams to deploy reliable, scalable, and governed GenAI capabilities using Amazon Bedrock and Cortex, with a strong emphasis on evaluation, guardrails, and production-grade MLOps.

Sr. Manager of Software Engineering for an AI/ML Solutions technology team focused on building and enhancing AI/ML platforms, Gen AI use cases, LLM fine-tuning, and multi-agent orchestration. The role involves hands-on code development, team management, and adopting best practices in software engineering and MLOps.

Develop and deploy agentic AI applications and autonomous AI agents using LLMs, prompt engineering, RAG, and fine-tuning, with a focus on corporate environments and AWS technologies.

Senior Lead Security Engineer focused on designing and delivering secure AI solutions for cyber use cases, including LLM/RAG services and ML pipelines. Responsibilities include establishing security standards, building evaluation harnesses, partnering with platform teams, implementing monitoring, and collaborating with governance. The role emphasizes shipping secure, reliable AI features with clear metrics and post-deployment monitoring, and driving a roadmap of key capabilities.

Product Manager (VP level) for AI-enabled automation in a payments platform, focusing on defining product strategy, driving roadmap, and leading PoCs for ML (anomaly detection) and LLM-based systems (RAG, agentic orchestration). Responsibilities include translating business needs into requirements, partnering with engineering on LLM/RAG solutions, defining success metrics, and managing end-to-end delivery in a complex, regulated environment.

JPMorgan Chase is seeking an Applied AI/ML Vice President for their Global Private Bank. This role involves owning the full lifecycle of high-impact models for wealth management, lending, and advisory, from problem framing to production deployment. The position requires expertise in NLP, LLM fine-tuning, RAG, prompt engineering, and multi-step AI agents, with a focus on building AI-native capabilities at scale within a regulated financial services environment.

This role focuses on building and deploying AI/ML/LLM/GenAI solutions, with a strong emphasis on fine-tuning generative models for specific use cases, building AI agents, and implementing RAG-based solutions. The role also involves developing data pipelines, evaluating models, and communicating results.

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.

Senior Lead Architect role focused on designing and developing an AI/ML platform, managing engineering teams, and driving the adoption of AI/ML solutions within financial services. The role involves overseeing the end-to-end lifecycle of AI/ML projects, ensuring scalability, performance, and compliance.

Senior Associate, AI ML Platform Engineering role at JPMorgan Chase, focused on building products for MLOps, automated governance, and ML data development. The role involves designing, developing, and deploying GenAI and Agentic AI solutions, including RAG-based systems, chat experiences, and tool-using agents. Responsibilities include engineering production-grade services, building data pipelines, applying MLOps practices, and implementing robust testing and observability for AI services. Requires strong software engineering skills in Java/Python, cloud experience (AWS), and familiarity with LLM application patterns.

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.

Lead data labeling initiatives for financial industry ML models, focusing on creating reliable datasets, managing annotation operations, and driving innovation in data quality and evaluation, including LLM-as-judge and agentic workflows.

Lead a team of software engineers to architect and develop an enterprise-grade Agentic AI platform, focusing on multi-agent orchestration, tool integration, memory, RAG, guardrails, observability, and evaluation. This role requires strong technical leadership in AI agents and people management skills to drive strategic vision and hands-on work.

Lead the design, development, and production deployment of AI/ML solutions for image classification, text categorization, and data extraction from scanned documents using computer vision and NLP models. Architect and implement scalable ML training and inference pipelines on AWS SageMaker, integrating with microservices and establishing MLOps practices. Build and manage a team of ML engineers and applied scientists.

Lead a team of data scientists in building and deploying advanced AI solutions for image classification, text categorization, and intelligent data extraction from scanned documents within the healthcare provider team at JPMorgan Chase. The role involves managing the full ML lifecycle, from prototyping to production deployment on AWS EKS, with a focus on multimodal document understanding.

Senior Lead Software Engineer focused on ML and GenAI solutions within Public Cloud Engineering at JPMorgan Chase. The role involves leading architecture, development, and production deployment of ML/LLM solutions, applying modern GenAI workflows, and ensuring responsible AI practices. Responsibilities include designing and implementing end-to-end ML/LLM solutions, productionizing models on public clouds using Kubernetes, establishing evaluation methodologies, and collaborating with stakeholders.

Senior Applied AI/ML Engineer to build and operate LLM-driven applications and ML products in a regulated fintech environment. Focus on agentic frameworks, prompt optimization, and fine-tuning LLMs, with a secondary focus on post-training techniques.

Senior Associate Data Scientist focused on applied AI/ML, specifically GenAI and LLMs, for fintech. Responsibilities include designing, developing, and deploying AI systems, integrating GenAI into platforms, optimizing performance, and ensuring responsible AI governance and compliance. Requires strong Python, ML framework, and MLOps experience, with a focus on agentic workflows and production deployment.

Senior Associate Data Scientist role in JPMorgan's AWM Risk Analytics Group, focusing on developing and deploying AI/ML models for risk management. Responsibilities include identifying use cases, leading model development (NLP, LLMs), prompt engineering, quantization, evaluation, data onboarding, model optimization, and contributing to risk methodologies. Requires experience with Python, SQL, R, PyTorch/TensorFlow, AWS, and frameworks like LangChain.

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.