Executive Director - Principal Architect

JPMorgan Chase & Co.•Jersey City, NJ

16h•$204,250 - $285,000

About The Position

As an Executive Director of Architecture & Engineering at JPMorgan Chase within Asset and Wealth Management, you define and drive the technical vision, architecture strategy, and engineering standards across multiple business-critical platforms. You bring executive leadership with deep architectural authority and code-level credibility, owning the technical north star with a strong point of view on agentic AI–enabled engineering, platform modernization, and enterprise-scale architecture governance.

Requirements

Obtain 10 plus years of experience in software engineering & architecture, technical leadership with progressive responsibility leading architecture/engineering teams at scale.
Proven senior/principal architect experience defining enterprise architecture vision and governing technology decisions across multiple lines of business; demonstrated success building and retaining high-caliber architecture/engineering leaders.
Hands-on architectural leadership to modernize complex systems at scale—driving CI/CD, automated testing, infrastructure-as-code, and secure SDLC controls; introducing AI/automation into engineering workflows with clear safety, quality, and measurable outcomes, including deploying agentic AI (architecture co-pilots, coding/review agents, automated conformance checking, release automation, incident-response agents) with operating model design and an adoption strategy.
Deep expertise in modern architecture patterns and distributed systems, including cloud-native design, microservices, event-driven and domain-driven design, API design, and data architecture; strong code/architecture review rigor and ability to solve deep technical problems alongside delivery teams.
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 scalable platforms while meeting resiliency, security, and auditability requirements.
Advanced knowledge of software architecture, application development, and technical processes with considerable in-depth knowledge in one or more technical disciplines (e.g., cloud, artificial intelligence, machine learning, mobile, etc.)
Experience applying expertise and new methods to determine solutions for complex architecture problems in one or more technical disciplines

Nice To Haves

Experience deploying agentic AI in engineering workflows (architecture co-pilots, coding/review agents, automated conformance checking, release automation, incident-response agents), including operating model design and adoption strategy
Experience with financial services domain architecture: trading, portfolio management, client lifecycle, or wealth management platforms
Active hands-on engagement with modern technology (coding, prototyping, architecture spikes) strongly preferred

Responsibilities

Define the architecture strategy for AI-native engineering - how agentic AI reshapes system design, development, testing, deployment, and operations across the SDLC
Establish AI-enabled patterns: spec-first development, agent-driven code generation with architectural constraint enforcement, automated conformance testing, AI-assisted capacity modeling
Define and enforce guardrails and governance for AI in engineering: human-in-the-loop approvals, design traceability, prompt/code hygiene, architectural fitness functions, and measurable quality gates
Build a culture of "architects who can still dive into code" - unblocking teams, raising the bar on design and implementation quality, and mentoring through hands-on engagement
Cloud-native transformation, API-first design, event-driven and domain-driven architectures, and data mesh patterns - with risk-managed execution
Applies enterprise-authorized AI capabilities within the work environment to accelerate architecture analysis, roadmap development, and design decisioning, with human-in-the-loop validation and appropriate handling of sensitive data.
Lead architecture governance, establishing principles, reference architectures, and decision frameworks that enable consistent, high-quality delivery at enterprise scale
Drive architecture simplification and rationalization - reducing technical debt, eliminating redundancy, and accelerating time-to-market
Establishes reuse-first AI-enabled engineering patterns and governance across SDLC/toolchain practices, ensuring traceability/auditability, resiliency, and security controls.