Executive Director - Principal Software Engineer - AI, NLP

If you are looking for a game-changing career, working for one of the world’s leading financial institutions, you’ve come to the right place.

As a Principal Software Engineer at JPMorganChase within the Asset Wealth Management, Client Onboarding Team, you provide expertise and engineering excellence as an integral part of an agile team to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. Leverage your advanced technical capabilities and collaborate with colleagues across the organization to drive best-in-class outcomes across various technologies to support one or more of the firm’s portfolios.

We are seeking a visionary Executive Director - Principal Software Engineer with extensive experience of applied experience in software engineering and deep expertise in advanced AI and agentic system development. This leader will be responsible for architecting and delivering AI-native, autonomous agentic AI solutions that transform client onboarding and operational workflows across the organization. The ideal candidate brings a proven track record of designing production-grade agentic AI frameworks — including multi-agent orchestration, retrieval-augmented generation (RAG) pipelines, dynamic tool-use agents, and LLM-powered reasoning systems — while building durable, reusable software frameworks leveraged across teams and functions. They will serve as the organization’s foremost subject matter expert on agentic AI, advising cross-functional teams on agent safety, prompt engineering, model evaluation, and responsible AI deployment, and will influence senior stakeholders across business, product, and technology on the strategic adoption of autonomous AI capabilities.

Job responsibilities

• Creates complex and scalable coding frameworks using appropriate software design frameworks
  Develops secure and high-quality production code, and reviews and debugs code written by others
• Lead the integration of intelligent, self-directed agents into existing enterprise systems, champion agile delivery practices, and translate complex AI concepts into measurable business outcomes for executive audiences.
• Architects and governs agentic AI-enabled engineering workflows (using enterprise-authorized tools within the work environment) to improve delivery speed, code quality, and operational outcomes at scale (e.g., AI-driven PR review assistance, test generation/maintenance, release readiness checks, incident triage and root-cause acceleration), while defining guardrails for validation, security, resiliency, and reuse across teams.
• 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 at scale.
• Advises cross-functional teams on technological matters within domain of expertise
• Serves as the function’s go-to subject matter expert
• Contributes to the development of technical methods in specialized fields in line with the latest product development methodologies
• Creates durable, reusable software frameworks that are leveraged across teams and functions
  Influences leaders and senior stakeholders across business, product, and technology teams

Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and 12 + years applied experience
• Design, develop, and maintain scalable applications using Python and Java/J2EE, hands-on experience with agentic AI frameworks, and deep knowledge of NLP, ML, and cloud-native AI deployment on AWS (including SageMaker and Bedrock).
• Experience leading AI-powered products as a Product Owner or Product Manager is required, along with a strong understanding of financial services.
• Lead the integration of AI technologies into existing systems, utilizing Natural Language Processing (NLP) and Machine Learning (ML) frameworks to enhance client onboarding processes and improve user experience. Collaborate with data scientists to develop and deploy predictive models.
• Implement cloud-based solutions on AWS, leveraging services such as EC2, S3, and Lambda. Champion agile methodologies within the team, facilitating sprint planning, daily stand-ups, and retrospectives to ensure timely delivery of high-quality software
• Expert in one or more programming language(s)
• Experience applying expertise and new methods to det…