Senior Lead Architect: Solution Architecture

JPMorgan Chase & Co.; Jersey City (NJ); On-site; USD 180,000 - 240,000; Full time

Job summary

JPMorgan Chase & Co. within Corporate Technology Data Strategy & Architecture seeks a Senior Lead Architect to design enterprise-scale AI/ML and data engineering solutions.

You will guide architecture governance, set technical direction, and ensure security, resiliency, and regulatory compliance across software applications and platform products. You will lead governance, collaborate with stakeholders, and drive adoption of AI-enabled engineering patterns, multi-agent systems, and cloud-native

Qualifications

• Formal training or certification on architecture concepts and 5+ years AI/ML, cloud, and data engineering.
• 12+ years of hands-on system design, development, testing, and operations.
• Proven production AI/ML system design with LLMs, embeddings, and agentic architectures.
• Experience evaluating model outputs for safety, accuracy, and latency in regulated environments.
• Proficiency in Java and Python.
• Deep knowledge of software architecture across cloud, AI/ML, and data engineering.
• Knowledge of relational and NoSQL databases, data lakes, Spark/PySpark, Databricks, Snowflake.
• Experience with microservices, API design, Kafka, Redis, Memcached, and observability/orchestration tools.
• Ability to evaluate and integrate AI-enabled capabilities into enterprise-grade architectures with resiliency, security, and auditability.
• Cloud-native experience; ability to tackle complex design challenges independently.
• Strong judgement and communication to influence technical direction.

Responsibilities

• Represent product families in governance bodies and propose architecture enhancements.
• Provide strategic technical guidance to stakeholders, engineering teams, contractors and vendors.
• Leverage AI/ML capabilities to accelerate analysis, decisions, and delivery with human-in-the-loop validation.
• Guide evaluation and integration of current and emerging technologies in AI/ML and cloud-native solutions.
• Drive architectural decisions impacting product design, functionality, and operations with AI patterns.
• Develop secure, high-quality production code for data-intensive AI apps and review peers' code.
• Act as SME in data engineering, platform architecture, and AI/ML; contribute to engineering community.
• Establish reuse-first AI-enabled engineering patterns with traceability, auditability, and security controls.
• Architect and govern agentic AI systems with multi-agent workflows and human-in-the-loop controls.
• Lead AI risk governance design, observability, and explain requirements for production AI systems.

Skills

AI/ML architecture experience

System architecture

Java

Python

AI/ML systems design

Model evaluation

Cloud-native design

Software architecture

Relational/NoSQL databases

Microservices/API design

Kafka

Observability tools

Orchestration tools

AI integration

Communication skills

Tools

LangChain

LangGraph

CrewAI

Triton

AWS Bedrock

Azure OpenAI

Databricks

Snowflake

Kubernetes

Airflow

Temporal

Job description

Are you passionate about shaping the future of technology and driving transformative business impact in financial services? Join JPMorganChase 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 NoSQL 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 (LangChain, LangGraph, 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 financial services, especially regarding AI use in decision-making.
• Knowledge of the financial services industry and their IT systems.