at J.P. Morgan
Bulge Bracket Investment BanksPosted 7 days ago
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**Tech Project Manager II** Drive complex tech projects in Asset & Wealth Management, managing resources and budgets to deliver business objectives. Utilize broad tech knowledge, enterprise AI capabilities, and Agile methodologies to navigate ambiguity and foster productive stakeholder relationships. Requires 2+ years of technical project/program management experience, AI familiarity, and strong communication skills. Lead projects, leverage AI for acceleration, and promote reuse-first practices in our dynamic environment.
- Compensation
- Not specified
- City
- Not specified
- Country
- United States
Currency: Not specified
Full Job Description
Location: Plano, TX, United States
Embrace the challenge of steering complex tech projects, fostering growth and technical excellence in a dynamic environment.
As a Technical Project Manager II in
As a Technical Project Manager II in
Asset & Wealth Management/
Asset & Wealth Management Tech & OPS, you will play a pivotal role in leading complex technology projects and programs that drive business goals and enhance the firm's technological capabilities. You will leverage your broad knowledge of technical principles and practices to develop innovative solutions, while effectively managing resources, budgets, and cross-functional teams. Your analytical reasoning and adaptability skills will enable you to navigate through ambiguity and embrace change. By fostering productive relationships with stakeholders and clients, you will contribute to the firm's overall growth and success. Your excellent communication skills and ability to influence others will be crucial in driving mutually beneficial outcomes and managing risks in line with the firm's policies and practices.
Job responsibilities
Job responsibilities
- Analyze and breakdown complex business, technical, and operational objectives into manageable tasks and activities, applying critical thinking and problem-solving skills
- Uses enterprise-authorized AI capabilities within the work environment to accelerate project planning and risk synthesis (e.g., drafting plans, RAID, and status narratives), validating outputs and handling data according to sensitivity requirements.
- Support the optimization of allocated resources, including people, budget, and technology, to effectively plan, schedule, and progress project and/or program initiatives
- Participate in stakeholder management, fostering productive working relationships with cross-functional teams and clients to drive mutually beneficial outcomes
- Assist in risk management by making informed decisions in line with the firm's risk management practices and policies, ensuring project success and compliance
- Promotes reuse-first, AI-assisted practices for project governance artifacts and reporting, ensuring human review and alignment to delivery standards.
- Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team
- Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation
- Provide clear, consistent communication and reporting: Run operating rhythms (standups, sprint ceremonies, stakeholder reviews), publish status updates/dashboards, and escalate decisions/risks early; strong written and verbal communication is required.
- Apply strong technical fluency to translate between business needs and engineering execution: Write/clarify requirements and acceptance criteria, facilitate solution discussions, and familiar with systems/APIs/integrations, CI/CD, and production support concepts enough to drive trade-offs and sequencing.
- Drive disciplined delivery practices and continuous improvement: Use Agile/Scrum/Kanban methodologies, define/track delivery metrics, manage change control, and conduct retros/postmortems.
Required qualifications, capabilities, and skills
- 2+ years of experience or equivalent expertise in technical program management, leading complex technology projects and programs. Formal training or certification on technical program management concepts and advanced applied experience.
- Demonstrated experience using enterprise-authorized AI capabilities within the work environment to support technical program management workflows with strong validation habits and awareness of data sensitivity.
- Ability to review and validate AI-assisted plans, risks, and recommendations before use, escalating when uncertain and following data handling expectations.
- Proven ability to utilize analytical reasoning and problem-solving techniques to break down objectives into manageable tasks
- Communication: Excels at written and verbal communication; experienced in communicating to stakeholders (emails, MS Teams, banners) on pertinent information to prevent siloing of necessary information. Experience creating and updating user documentation.
- Leadership and Ownership: Proactively steps into ambiguity, identifies what needs to be done, and takes ownership of delivering project outcomes with minimal oversight.
- Project Planning & Tracking Skills: Effectively plans project timelines and proactively tracks all dependencies, risks, and cross-team handoffs, ensuring nothing is missed and no follow-up is required from leadership.
- Experience in resource optimization and/or resource planning
- Prior experience managing diverse sets of stakeholders, establishing productive working relationships with cross-functional teams and clients, and managing project governance
- Demonstrated experience leading effective use of approved AI-assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security
- Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices
Preferred qualifications, capabilities, and skills
- Scrum Master experience or CSM certification
- Utilization of AI to improve and drive success
