Join us as we embark on a journey of collaboration and innovation, where your unique skills and talents will be valued and celebrated. Together we will create a brighter future and make a meaningful difference.

As a Senior Principal Architect - Artificial Intelligence at JPMorgan Chase on Global Technology’s Enterprise Architecture team, you will help shape, lead adoption, and operate the firm’s Artificial Intelligence Architecture Domain.

You will provide specialized expertise to influence the target state architecture and strategy of the domain, and work across teams to educate and build consensus to drive domain strategies. You will lead the AI domain’s architecture review boards in evaluating, adjudicating, onboarding, and adopting technologies to be used by development teams to compose their business systems. You will advise, inform, and assist on decisions about the strategy, roadmaps, operationalization, and productization of those technologies that will be scaled and made available firmwide.

Responsibilities

Advise and influence portfolio owners and operate architecture review boards on developing and maintaining AI tools across a large enterprise, including selection, integration, and retirement; includes stakeholders of varying degrees of technical or business orientationServe as a subject matter expert on AI at JPMC, with special emphasis on delivering technology capabilities and managing sprawl in priority areas such as AI Applications, Generative AI, AI Infrastructure DevelopmentTranslates highly complex technical issues, trends, and approaches to leadership to drive the firm’s AI technology strategy and enable leaders and technology requestors from solution teams to make strategic, well-informed decisions about target state offerings and solution architectureCollaborate with peers from other domain portfolios to drive improvement in rationalization practices in Global TechnologyEvaluate emerging AI technologies, platforms, and tools for fit, scalability, and risk; may include proof-of-concept initiatives and technology assessmentsDevelop and maintain a strategic roadmap for AI technology components aligned with business objectivesDesign scalable, secure, and robust AI architectures (including data pipelines, model deployment, monitoring, and governance)Establish architectural standards, best practices, and governance frameworks for AI solutionsIdentify and mitigate risks related to AI (e.g., data privacy, model bias, regulatory compliance), and ensure AI solutions adhere to internal and external compliance requirementsMonitor and optimize the performance, scalability, and cost-effectiveness of AI solutions and SaaS providers

 

Required qualifications, skills and capabilities

Formal training or certification on software engineering concepts and 10+ years applied experienceBachelor's or master's degree in computer science, data science, artificial intelligence, engineering, mathematics, or a related field, or equivalent experience of hands-on experience in AI system design, application development, model development, deployment, testing, and operational stability. Proven experience influencing across functions and teams to deliver modern architectureExperience with AI agentic architectures, prompt design, and context engineeringDeep technical expertise and hands-on experience in the AI/ML domain, including relevant platforms, tools, and regulatory frameworks such as TensorFlow, PyTorch, MLOps, Responsible AI, GDPR, CCPA, and AI Act.Demonstrable skills in AI/ML concepts, algorithms, frameworks, software architecture, and engineering principlesExpertise in architecture and design for AI systems, machine learning applications, data pipelines, infrastructure, and SaaS-based AI/ML architectures, including data and process integration; Advanced knowledge of AI/ML model development, software architecture, technical processes, system engineering principles, cloud AI platforms, and Infrastructure-as-Code for cloud-based workloadsExperience leading AI architecture strategy, governance, standards development, and managing technology portfolios or cross-functional technology initiatives; Proven track record in designing and deploying enterprise-scale AI solutionsDemonstrated ability to translate business problems into practicable AI solutions using structured, user-centered, and iterative approaches grounded in system engineeringExceptional communication skills with the ability to inform and persuade senior leaders and executives on AI strategy and adoptionExperience collaborating with cross-functional teams, including data scientists, engineers, product managers, and business stakeholders, and building effective relationships to drive solution development; Knowledge of deployment strategies for both open-source and managed models including expertise in material and immaterial model governance

 

Preferred Qualifications, Skills, and Expertise

Advanced certifications in AI/ML, cloud architecture, or enterprise architecture (such as TOGAF or AWS Certified Solutions Architect) are preferred

Experience driving change and adoption of new technologies within large organizations preferred