As a Principal Architect at JPMorganChase within Asset and Wealth Management you provide expertise to enhance and develop architecture platforms based on modern cloud-based technologies, as well as support the adoption of strategic global solutions. As a Generative AI Executive Director, you will lead the design and delivery of production-grade LLM systems that power mission-critical products for thousands of professionals. Your technical leadership will empower teams to innovate and accelerate the adoption of AI at scale. You will collaborate with cross-functional teams to bridge advanced AI research with robust engineering, ensuring our solutions are reliable, secure, and built for real business impact.

Job Responsibilities:

• Architects scalable APIs and agentic workflows, enabling automation and efficiency across the firm
• Architects and delivers production LLM-based systems for text, image, speech, and video applications
• Leverages enterprise-authorized AI capabilities within the work environment to accelerate architecture analysis and decisioning across the product family, with human-in-the-loop validation and appropriate handling of sensitive data.
• Establishes reuse-first AI-enabled engineering patterns and governance across SDLC/toolchain practices, ensuring traceability/auditability, resiliency, and security controls.
• Collaborates closely with ML Engineering, Product Management, and Cloud Engineering to ensure reliability and security
• Bridges advanced AI research with robust engineering to build innovative, scalable, production-ready solutions
• Drives results with an entrepreneurial mindset in a fast-paced, high-impact environment
• Actively advocates for firmwide frameworks, tools, and practices of the Software Development Life Cycle

Required Qualifications, Capabilities, and Skills:

• Formal training or certification on software engineering concepts and 7+ years applied experience
• Holds a Masters or possesses equivalent experience in Computer Science, Mathematics, Statistics, or a related quantitative discipline
• Experience with cloud platforms (AWS, Azure) and containerization (Docker, Kubernetes)
• Experience with Java, Python, Java Spring, ORM frameworks, Agentic AI frameworks (a2a, langGraph), messaging frameworks, unit and automated testing frameworks (BDD, Functional & Performance), and databases
• Demonstrates extensive hands-on experience in software engineering and ML engineering, with a proven track record of shipping production systems
• Demonstrated experience applying enterprise-authorized AI capabilities within the work environment in architecture and engineering workflows with strong validation habits and awareness of data sensitivity.
• Ability to evaluate and integrate AI-enabled capabilities into enterprise-grade architectures while meeting resiliency, security, and auditability requirements.
• Advanced knowledge of software architecture, applications, and technical processes with in-depth expertise in one or more technical disciplines (e.g., cloud, AI, ML, distributed systems)
• Architects and implements high-throughput, low-latency microservices with WebSocket, gRPC, REST, and GraphQL, including protocol buffer schema design, streaming endpoints, and load balancing
• Hands-on practical experience delivering system design, application development, testing, and operational stability

Preferred Qualifications, Capabilities, and Skills:

• Knowledge of advanced agentic workflows, including multi-agent coordination, stateful task management, and integration with enterprise event-driven architectures
• Agent Guardrails and Evaluation frameworks
• Excellent communication and presentation skills