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$162,000–$235,750.
Based on 239 similar postings.
Employer
About JPMorgan Chase
JPMorgan Chase & Co. is a global financial services firm and one of the largest banks in the world, offering investment banking, commercial banking, asset management, and consumer financial services.
JPMorgan Chase currently has
1117 open roles
on FindRole.
Listed pay typically runs
$186,160–$215,000
across 7 roles with salary data.
As a Senior Lead Architect: Solution Architecture within the Corporate Technology Data Strategy & Architecture organization, you will design and govern enterprise-scale architecture solutions for software applications and platform products. You will be responsible for architecting next-generation AI/ML systems, including LLM-based applications, embedding pipelines, vector stores, and agentic architectures with multi-agent workflows and tool-use patterns. Your daily work involves providing strategic technical guidance to stakeholders, developing production code, and establishing reuse-first engineering patterns that ensure security and regulatory compliance in financial services. You will utilize technologies such as Java, Python, Spark, Databricks, Snowflake, Kafka, Redis, and orchestration tools like Airflow or Temporal. The role focuses on solving complex challenges in data engineering, cloud-native architecture, and AI risk governance while ensuring high-quality, resilient systems for data-intensive applications within a regulated environment.
Design and govern enterprise-scale architecture solutions for software applications and platform products.
Architect and govern agentic AI systems including multi-agent workflows and human-in-the-loop controls for regulated environments.
Develop secure, high-quality production code for data-intensive and AI-driven applications while reviewing others' code.
Establish and govern reuse-first, AI-enabled engineering patterns across the software development life cycle.
Lead AI risk governance design, observability, and explainability requirements for production AI systems.
Provide strategic technical guidance to business stakeholders, engineering teams, contractors, and vendors.
Evaluate and integrate emerging technologies like LLMs and cloud-native solutions into enterprise architectures.
Represent product families in technical governance bodies to improve architecture and AI risk management practices.
What we're looking for
Formal training or certification on architecture concepts.
5+ years of 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.
Expertise in designing production AI/ML systems including LLM applications, embedding pipelines, vector stores, and agentic architectures.
Advanced proficiency in programming languages such as Java and Python.
Knowledge of relational and NoSQL databases, data lake architectures, and large-scale processing technologies like Spark, Databricks, or Snowflake.
Experience with microservices, API design, Kafka, Redis, Memcached, observability tools, and orchestration tools like Airflow or Temporal.
Experience with LLM orchestration frameworks (LangChain, LangGraph, CrewAI) and model serving infrastructure (Triton, AWS Bedrock, Azure Open AI) (preferred).
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