Senior Lead Architect: Solution Architecture

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Category:
Architecture

Job Schedule:

Full time

Posted Date: T16:32:10+00:00

Job Shift:

Base Pay/Salary:
Jersey City,NJ $-$

Are you passionate about shaping the future of technology and driving transformative business impact in financial services? Join JPMorgan

Chase as a Senior Lead Architect and help us deliver innovative, high-quality solutions that leverage advanced AI, machine learning, and data engineering capabilities.

As a Senior Lead Architect at JPMorgan Chase within the Corporate Technology Data Strategy & Architecture organization, you will play a pivotal role in designing and governing enterprise-scale architecture solutions for software applications and platform products You will drive significant business impact by architecting next-generation AI/ML systems, influencing technology direction, and ensuring our solutions meet the highest standards of security, resiliency, and regulatory compliance.

Job responsibilities

* Represent product families in technical governance bodies, proposing enhancements to architecture governance and AI risk management practices.

* Provide strategic technical guidance to business stakeholders, engineering teams, contractors, and vendors, fostering a collaborative and innovative environment.

* Leverage enterprise-authorized AI/ML capabilities-including LLMs, agentic systems, and embedding pipelines-to accelerate architecture analysis, decisioning, and solution delivery, with robust human-in-the-loop validation and sensitive data handling.

* Guide evaluation and integration of current and emerging technologies, influencing peers and decision-makers to adopt leading-edge AI/ML and cloud-native solutions.

* Drive architectural decisions impacting product design, application functionality, and technical operations, with a focus on AI-enabled engineering patterns and governance.

* Develop secure, high-quality production code for data-intensive and AI-driven applications; review and debug code written by others to ensure best practices.

* Serve as a subject matter expert in data engineering, platform architecture, and AI/ML, actively contributing to the engineering community and advocating firmwide SDLC frameworks.

* Establish and govern reuse-first, AI-enabled engineering patterns across SDLC/toolchain practices, ensuring traceability, auditability, resiliency, and security controls.

* Architect and govern agentic AI systems-including multi-agent workflows, tool-use patterns, and human-in-the-loop controls-suitable for regulated financial services environments.

* Lead AI risk governance design, observability, and ability to explain requirements for production AI systems, shaping enterprise approaches to AI agent orchestration, inter-agent communication, and state management at scale.

Required qualifications, capabilities, and skills

* Formal training or certification on architecture concepts and 5+ years applied experience in AI/ML, cloud, and data engineering

* Minimum 12+ years of hands-on experience in system design, application development, testing, and operational stability.

* Demonstrated expertise in designing and deploying production AI/ML systems, including LLM-based applications, embedding pipelines, vector stores, and agentic architectures with tool use, memory, and multi-step reasoning.

* Experience evaluating model outputs for safety, accuracy, and latency in regulated environments.

* Advanced proficiency in programming languages such as Java and Python.

* Deep knowledge of software architecture, applications, and technical processes within disciplines such as cloud, artificial intelligence, machine learning, and data engineering.

* Working knowledge of relational and No

SQL databases, data lake architectures, and large-scale data processing technologies (e.g., Spark/PySpark, Databricks, Snowflake).

* Experience with microservices, API design, Kafka, Redis, Memcached, observability tools (Dynatrace, Splunk, Grafana), and orchestration tools (Airflow, Temporal).

* Ability to evaluate and integrate AI-enabled capabilities into enterprise-grade architectures, meeting resiliency, security, and auditability requirements.

* Practical cloud-native experience and ability to tackle complex design and functionality challenges independently.

* Strong judgment and communication skills to influence technical direction across teams and stakeholders.

Preferred qualifications, capabilities, and skills

* Experience with modern data technologies such as Databricks or Snowflake.

* Hands-on experience with LLM orchestration frameworks (Lang Chain, Lang Graph, CrewAI, or equivalent) and model serving infrastructure (Triton, AWS Bedrock, Azure Open AI).

* Familiarity with AI evaluation and observability-red-teaming, evals frameworks, prompt drift detection, and cost/latency monitoring for LLM workloads.

* Understanding of agentic design patterns:
React, plan-and-execute, reflection loops, and how to constrain agent autonomy in high-stakes financial workflows.

* Awareness of the AI regulatory landscape in…