AI Lead Technical Program Manager

Make your mark by leading high-impact technology programs that help teams deliver meaningful business outcomes. Join a collaborative environment where you will influence direction, remove delivery friction, and strengthen end-to-end execution. Bring your program leadership and technical depth to grow your career through challenging work and broad stakeholder exposure. As a Lead Technical Program Manager at JPMorganChase within the Enterprise Technology’s Ai/ml & Data Platforms team you will drive the successful delivery of complex technology programs that support business objectives. You will translate technical requirements into clear plans, coordinate cross-functional teams, and manage delivery risks to achieve predictable outcomes. You will apply strong judgment to navigate ambiguity, adapt to change, and maintain alignment between technology delivery and business priorities. You will communicate progress and decisions clearly to stakeholders and leaders to enable timely trade-offs. You will uphold disciplined execution practices to support high-quality, professional service delivery. This London-based role partners closely with engineering, product, and business stakeholders to deliver measurable results across multiple workstreams. You will be accountable for building integrated plans, aligning dependencies, and ensuring delivery governance is effective and lightweight. You will help teams use approved automation and artificial intelligence tools responsibly to improve planning speed and reporting quality, while maintaining human oversight. Success requires strong stakeholder leadership, comfort operating across multiple teams, and a consistent focus on outcomes. Job Responsibilities Drive end-to-end delivery of complex technology programs, from initiation through execution and closure, to achieve committed outcomes. Define program scope, objectives, deliverables, milestones, and dependencies with engineering, product, and business partners to maintain alignment to business goals. Develop and maintain integrated delivery plans, including resourcing, timelines, critical path, and inter-team dependencies to support predictable execution. Identify delivery risks, issues, and constraints early, and implement mitigation and contingency actions to maintain momentum. Lead program governance and executive-ready reporting, ensuring status, decisions, and trade-offs are clear, timely, and traceable. Apply approved automation and artificial intelligence capabilities to accelerate planning and risk synthesis, validate outputs before use, and handle data according to sensitivity expectations. Measure program performance using agreed metrics, analyze drivers of variance, and implement data-informed improvements to increase delivery efficiency and reliability. Champion modern delivery practices and continuous improvement, reinforcing consistent ways of working across teams and workstreams. Required qualifications, capabilities, and skills 5+ years of experience in technical program management delivering complex technology initiatives in a large organization. Demonstrated ability to build and manage integrated program plans (scope, milestones, dependencies, resourcing, and timelines). Demonstrated experience leading cross-functional stakeholders and influencing decisions across engineering, product, and business teams. Proven ability to identify and manage delivery risks and issues, including escalation and contingency planning. Experience using approved workplace automation and artificial intelligence tools to support program workflows, with documented habits of validating outputs before adoption. Strong written and verbal communication skills, including the ability to produce clear executive updates and decision logs. Strong analytical and problem-solving skills to break down complex objectives into sequenced deliverables and measurable outcomes. Preferred qualifications, capabilities, and skills Experience delivering AI-driven programs in banking/financial services or similarly regulated industries. Expertise on the AI and data product lifecycle, spanning from data discovery, data processing, model development, model deployment, and model monitoring Experience partnering with risk, compliance, control, and internal audit stakeholders to implement change in highly governed environments Experience in organizational operation, Excel data analysis, and organization budgeting & planning Microsoft (Azure AI Engineer Associate), Google (Professional Machine Learning Engineer), Amazon (AWS Certified AI Practitioner), AWS Cloud Practitioner Certification, or Microsoft Azure Fundamentals certifications, a plus