Principal Architect, AI-Native Engineering Platforms
JPMorgan Chase · Jersey City, United States · 1mo ago
If you are excited about shaping the future of technology and driving significant business impact in financial services, we are looking for people just like you. Join our team and help us develop game-changing, high-quality solutions.
As a Principal Architect at JPMorganChase within Asset and Wealth Management, you are an integral part of a team that works to develop high-quality architecture solutions for various software applications and platform products. You drive significant business impact and help shape the target state architecture through your capabilities in multiple architecture domains.
As an Executive Director of Architecture & Engineering, 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.
Job 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
- Lead cloud-native transformation, API-first design, event-driven and domain-driven architectures, and data mesh patterns with risk-managed execution
- Apply 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
- Establish reuse-first AI-enabled engineering patterns and governance across SDLC/toolchain practices, ensuring traceability/auditability, resiliency, and security controls
Required qualifications, capabilities, and skills
- Formal training or certification on software engineering concepts and 10+ years applied experience
- 10+ 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
Preferred qualifications, capabilities and skills
- 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