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Chase · 3 weeks ago

Senior Principal Architect - Artificial Intelligence

575 Washington Blvd, Jersey City, NJ, 07310, US

Full-time

Onsite

Senior Level, Lead/Staff

10+ years exp

Chase is embarking on a journey of collaboration and innovation, seeking a Senior Principal Architect - Artificial Intelligence to lead the firm's AI Architecture Domain. This role involves shaping and influencing the AI technology strategy, advising on architecture standards, and collaborating across teams to enhance AI capabilities within the organization.

BankingFinancial Services

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 orientation

Serve 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 Development

Translates 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 architecture

Collaborate with peers from other domain portfolios to drive improvement in rationalization practices in Global Technology

Evaluate emerging AI technologies, platforms, and tools for fit, scalability, and risk; may include proof-of-concept initiatives and technology assessments

Develop and maintain a strategic roadmap for AI technology components aligned with business objectives

Design scalable, secure, and robust AI architectures (including data pipelines, model deployment, monitoring, and governance)

Establish architectural standards, best practices, and governance frameworks for AI solutions

Identify and mitigate risks related to AI (e.g., data privacy, model bias, regulatory compliance), and ensure AI solutions adhere to internal and external compliance requirements

Monitor and optimize the performance, scalability, and cost-effectiveness of AI solutions and SaaS providers

Qualification

AI system designAI/ML domain expertiseAI architecture strategyData pipelinesTensorFlowPyTorchMLOpsResponsible AICloud AI platformsInfluencing skillsCommunication skillsCollaboration skills

Required

Formal training or certification on software engineering concepts and 10+ years applied experience

Bachelor'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 architecture

Experience with AI agentic architectures, prompt design, and context engineering

Deep 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 principles

Expertise 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 workloads

Experience 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 solutions

Demonstrated ability to translate business problems into practicable AI solutions using structured, user-centered, and iterative approaches grounded in system engineering

Exceptional communication skills with the ability to inform and persuade senior leaders and executives on AI strategy and adoption

Experience 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