Agent Specialist Lead - Vice President - Technical Product Manager - GenAI at JPMC Candidate Experience page

London, England, United Kingdom -

Full Time

Start Date

Immediate

Expiry Date

25 Jan, 26

Salary

0.0

Posted On

27 Oct, 25

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

AI, Machine Learning, Intelligent Systems, LLM-Powered Solutions, Multi-Agent Systems, Python, Cloud Platforms, Docker, Kubernetes, Microservices, GenAI, Performance Evaluation, Collaboration, Risk Controls, Innovation, Financial Services

Industry

Financial Services

Description

Join us to shape the future of Generative AI in the Commercial & Investment Bank. You will have the opportunity to work with cutting-edge technology and collaborate with talented teams across multiple business lines. Your expertise will help us deliver innovative agentic solutions that automate complex workflows and drive business impact. We value your technical depth, creativity, and ability to translate ideas into operational excellence. Be part of a team that is leading the way in AI adoption and transformation. As an Agent Specialist Lead in the GenAI Enablement Team within the Chief Analytics Office, you will advise and guide teams in designing, implementing, and scaling agentic systems that extend our Generative AI capabilities. You will work closely with stakeholders, product managers, data scientists, and engineering partners to operationalize LLM-powered agents that automate reasoning, retrieval, and workflow execution across the Commercial & Investment Bank. Your role will be central to driving the adoption of GenAI tools and frameworks, including our proprietary LLM Suite platform. You will help foster a collaborative and innovative team culture focused on delivering impactful AI solutions. Job Responsibilities: Lead the deployment, and support of LLM-powered agentic systems, ensuring scalability, observability, and high performance in production environments. Collaborate with business stakeholders to identify high-impact use cases and translate business requirements into agentic architectures integrated with existing data and workflow platforms. Provide technical guidance to cross-functional teams, fostering hands-on learning and effective collaboration across research, engineering, and product functions. Enhance agent orchestration, retrieval, and reasoning capabilities in partnership with engineering teams to improve performance, reliability, and resilience at scale. Work with AI researchers, ML engineers, and developers to advance agentic design, including dynamic planning, tool use, and multi-agent collaboration. Troubleshoot and optimize deployments, ensuring smooth implementation, compliance with risk controls, and continuous performance improvement. Required Qualifications, Capabilities, and Skills: Significant experience in AI, machine learning, or intelligent systems, with recent experience building or deploying LLM-powered or agentic solutions. Hands-on experience designing and implementing multi-agent systems using frameworks such as LangChain, LangGraph, AutoGen, or CrewAI, with practical understanding of LLM orchestration, retrieval augmentation (RAG), tool calling, and dynamic reasoning. Experience integrating agentic systems into enterprise data and workflow environments, ensuring robustness, and maintainability. Proficiency in Python, with experience extending orchestration components and building APIs or tool interfaces. Experience deploying AI systems on cloud platforms using Docker, Kubernetes, and microservices integration. Experience deploying and optimising GenAI and LLM-based systems, including performance evaluation and monitoring. Strong analytical foundation with the ability to reason about system performance, model behaviour, and control trade-offs. Proven ability to influence and align cross-functional teams through collaboration. Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Software Engineering or a related technical field required. Strong communication skills for technical and non-technical audiences. Preferred Qualifications, Capabilities, and Skills: Familiarity with risk controls and compliance in AI deployments. Ability to drive innovation in agentic system design and orchestration. Experience in financial services or enterprise environments. Track record of mentoring and developing talent in AI teams. Why Join Us? You will be part of a forward-thinking team driving the GenAI strategy for the Commercial & Investment Bank. We offer opportunities for career growth, hands-on learning, and the chance to make a meaningful impact through innovative AI solutions. Collaborate with experts, work on industry-leading projects, and help shape the future of AI at our firm.

Responsibilities

Lead the deployment and support of LLM-powered agentic systems while collaborating with business stakeholders to identify high-impact use cases. Enhance agent orchestration and troubleshoot deployments to ensure compliance and continuous performance improvement.