Bulge Bracket Investment Banks

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**Senior Lead Architect, Agentic AI Solutions Architect**: As a Senior Lead Architect, you'll shape and scale agentic AI solutions across a global enterprise. This role combines strategic architecture with hands-on delivery, driving business impact within the Corporate Sector's Employee Platforms. Key responsibilities include prototyping and implementing AI solutions, establishing reusable engineering patterns, and balancing future-facing architecture with measurable value deliveries. This role requires 5+ years of architecture experience, proficiency in one or more programming languages, and expertise in cloud, AI, or related technical disciplines. Bring your experience in agentic systems, public cloud implementations, and AI/ML foundations to influence technical direction and guide teams from concept to production. Join JPMorgan Chase today to make a significant impact on employee platforms serving 300,000+ users.

Compensation: Not specified
City: New York City
Country: United States

Full Job Description

Location: NY, United States

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 Senior Lead Architect at JPMorganChase within the Corporate Sector, Employee Platforms, 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.

You will help shape, prototype, and scale agentic AI solutions across a global enterprise serving more than 300,000 employees. This individual contributor role sits within the central Engineering and Architecture function of a 3000+ person technology organization, partnering horizontally across Employee Platforms to design intelligent, secure, and practical AI-enabled capabilities. You will work across domain architects, engineers, product teams, security, control functions, and platform owners to architect and build custom agentic systems, implement AI solutions in public cloud environments, and create reusable patterns that help teams provide employees innovative AI solutions that allow them to deliver at their highest potential. The role balances future-facing agentic architecture with hands-on delivery, helping Employee Platforms evaluate trade-offs, apply appropriate controls, and deliver measurable value through both custom and vendor AI capabilities.

Job responsibilities

Represents a product family in technical governance bodies and proposes improvements to architecture governance practices

Regularly provides technical guidance and direction to support the business and its technical teams, contractors, and vendors

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

Guides evaluation of current and new technologies using existing standards and frameworks, influencing peers and decision-makers to adopt leading-edge solutions where appropriate

Drives decisions that influence product design, application functionality, and technical operations and processes

Develops secure and high-quality production code, and reviews and debugs code written by others

Serves as a function-wide subject matter expert and contributes to the engineering community as an advocate of firmwide SDLC frameworks and practices

Establishes reuse-first AI-enabled engineering patterns and governance across SDLC/toolchain practices, ensuring traceability/auditability, resiliency, and security controls

Architect and build custom agentic systems that support Employee Platforms use cases across employee experience, workflow automation, knowledge discovery, service operations

Design prototypes, reference implementations, reusable patterns, and evaluation harnesses that help engineering teams move agentic AI capabilities safely from concept to production

Implement AI and agentic solution patterns in public cloud environments, with practical attention to APIs, data access, deployment automation, observability, resilience, and operational support

Required qualifications, capabilities, and skills

Formal training or certification on architecture concepts and 5+ years applied experience

Hands-on practical experience delivering system design, application development, testing, and operational stability

Advanced in one or more programming language(s) and deep expertise in software architecture, applications, and technical processes within one or more technical disciplines (e.g., cloud, artificial intelligence, machine learning, mobile, etc.)

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

Ability to tackle design and functionality problems independently with little to no oversight

Ability to evaluate current and emerging technologies to select or recommend the best solutions for the future state architecture

Strong judgment and communication skills to influence technical direction across teams

Agentic AI architecture: Hands-on experience architecting and building custom agentic systems, including tool use, orchestration, memory patterns, planning, autonomy boundaries, human-in-the-loop controls, and evaluation approaches

Public cloud implementation: Practical experience implementing AI, data, integration, or agentic solutions in public cloud environments

AI / ML foundations: Strong understanding of LLMs, RAG, embeddings, model selection, prompt design, multi-model orchestration, and responsible use of generative AI capabilities

Preferred qualifications, capabilities, and skills

Experience with vendor AI platforms and enterprise SaaS ecosystems, such as Microsoft Copilot, ServiceNow, Salesforce, Oracle HCM, OpenAI, Anthropic Claude, or similar platforms

Experience operating in a regulated enterprise environment, including financial services, healthcare, government, or other control-oriented industries

Familiarity with security, SaaS integration, AI governance, responsible AI practices, model risk concepts, and control frameworks for autonomous or semi-autonomous systems

Experience contributing to reusable architecture patterns, engineering standards, architecture communities, or internal enablement materials

Exposure to emerging agentic AI protocols, frameworks, and integration patterns, including MCP, A2A, LangGraph, CrewAI, or similar technologies

Mentor engineers and architects, contribute to architecture communities, and communicate complex AI architecture concepts in a clear, practical, and inspiring way

Communication and influence: Ability to explain complex technical tradeoffs clearly to engineering, product, architecture, security, and leadership stakeholders, with strong written architecture documentation skills

Drive significant business impact and help shape the target state architecture in multiple architecture domains

Full Job Description