Senior Lead Software Engineer, Data Strategy & Architecture

Salary: $61,000 - 101,000 per year Requirements:

• We require formal training or certification in software engineering concepts and at least five years of applied experience.
• We seek hands-on experience building and shipping production LLM applications and agentic systems with tool use, memory, and multi-step reasoning.
• We require advanced proficiency in one or more programming languages, particularly Python and/or Java.
• We expect deep experience with large-scale data processing, microservices, API design, and event streaming such as Kafka.
• We seek working knowledge of relational and NoSQL databases, vector stores, and data lake architectures.
• We require experience with caching technologies such as Redis or MemCached, observability tools such as Dynatrace, Splunk, or Grafana, and orchestration frameworks such as Airflow or Temporal.
• We expect proficiency in CI/CD, test-driven development, automation, and the full software development lifecycle.
• We seek a strong understanding of agile methodologies, application resiliency, and security best practices.
• We require practical cloud-native engineering experience with AWS, Azure, or GCP.
• We expect demonstrated experience leading the effective use of enterprise-authorized AI-assisted software development tools, including setting expectations for validating AI outputs for correctness, performance, and security.
• We seek a strong understanding of responsible AI use in engineering workflows, including data sensitivity, secure handling of inputs and outputs, and security and resiliency expectations; experience coaching senior engineers or leads on compliant usage patterns and controls is also required.
• Preferred qualifications include experience with LLM orchestration frameworks and model-serving infrastructure or managed endpoints such as AWS Bedrock or Azure OpenAI.
• We value familiarity with AI evaluation and observability practices, including evaluation frameworks, red-teaming, prompt drift detection, and cost and latency monitoring.
• We value an understanding of agentic design patterns and ways to constrain agent autonomy in high-stakes financial workflows.
• Preferred experience includes modern data platforms such as Databricks or Snowflake, and Spark/PySpark or large-scale big data processing.
• Knowledge of financial services technology systems and awareness of AI risk and regulatory considerations relevant to financial decision-making are advantageous.

• We develop secure, high-quality production code for data-intensive applications and platforms, and review and debug code written by others.
• We lead the end-to-end design and implementation of complex software features, from requirements through deployment and operational stability.
• We drive technical decisions that shape application design, functionality, performance, and reliability.
• We build and maintain agentic AI systems, including multi-agent workflows, tool integrations, and human-in-the-loop controls suited to regulated financial services.
• We implement LLM-based applications, including RAG pipelines, embedding workflows, vector store integrations, and model-serving infrastructure.
• We own the observability, evaluation, and safety of production AI systems, including prompt monitoring, output validation, cost tracking, and latency optimization.
• We identify and carry out opportunities to automate recurring issue remediation and strengthen operational stability.
• We design, develop, and troubleshoot creative software solutions to address complex and ambiguous problems.
• We mentor and coach junior and mid-level engineers, conduct code reviews, and share engineering best practices.
• We contribute to firmwide frameworks, tools, and software development lifecycle practices as active members of the engineering community.
• We promote and govern approved AI-assisted engineering practices across teams to improve code quality, delivery speed, and operational outcomes. This includes setting measurable validation standards for secure coding, peer review, and automated testing, and encouraging reuse of proven patterns and automation across the SDLC/TLM toolchain.
• We apply software development lifecycle toolchain capabilities, including approved AI-assisted development and automation tools, to increase the value delivered by automation at scale.

• Agentic AI
• AI
• Airflow
• API
• AWS
• Azure
• Big Data
• CI/CD
• Cloud
• Databricks
• Dynatrace
• GCP
• Grafana
• Support
• Java
• Kafka
• LLM
• Marketing
• NoSQL
• Python
• PySpark
• RAG
• Redis
• Security
• Snowflake
• Spark
• Splunk
• microservices
• Architect
• Model Serving

More:

We are hiring a Senior Lead Software Engineer for our Corporate Technology Data Strategy & Architecture organization, where you will join an agile team building trusted, secure, stable, and scalable technology products and delivering significant business impact. JPMorganChase serves consumers, small businesses, and corporate, institutional, and government clients, and operates across investment banking, consumer and commercial banking, financial transaction processing, and asset management. Our Corporate Functions teams span areas including finance, risk, human resources, and marketing, supporting the success of our businesses, clients, customers, and employees. We offer competitive total rewards and, for eligible roles, possible commission-based pay or discretionary incentives, alongside benefits that may include health care, wellness centers, retirement savings, backup childcare, tuition reimbursement, mental health support, and financial coaching. We are an equal opportunity employer committed to diversity, inclusion, and reasonable accommodations.

last updated 42 week of 2026