AI Lead Software Engineer

JPMorganChase • Jersey City, NJ

8d

About The Position

As an AI Lead Software Engineer at JPMorganChase within Corporate Technology, you will be a key technical leader on an agile team designing and delivering secure, scalable, high-performing technology solutions. You will partner with product, business, and engineering stakeholders to build strategic AI platforms that support the firm’s objectives.

The role leads software design and delivery, drives architectural decisions, and builds secure production services and data-intensive workflows. It also includes designing AI-enabled applications, such as those using retrieval-augmented generation and agentic workflows, with appropriate evaluation and guardrails. The engineer promotes enterprise-authorized AI-assisted engineering practices and automation while establishing validation standards for secure coding, peer review, and testing, and sharing effective patterns across the team.

Requirements

• Formal training or certification in software engineering concepts and at least 5 years of applied experience.
• Hands-on experience designing and delivering scalable, secure, resilient distributed systems in a production environment.
• Proficiency in Java and Spring Boot, with working knowledge of SQL and modern user interface frameworks such as React.
• Strong understanding of modern architecture patterns, including microservices, event-driven design, and API-first approaches.
• Experience building and operating solutions on public cloud platforms such as Amazon Web Services, including containerization and orchestration with Docker and Kubernetes.
• Experience implementing continuous integration and continuous delivery pipelines and Infrastructure as Code practices.
• Practical experience with API design and integration patterns such as REST and GraphQL, including security and performance considerations.
• Experience leading effective use of approved AI-assisted software development tools for coding, code review, test acceleration, or troubleshooting, and setting expectations for validating AI outputs for correctness, performance, and security.
• 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 engineers on safe, compliant adoption.

Nice To Haves

• Advanced expertise in object-oriented design, system design, and performance optimization for large-scale services.
• Experience with modern data and search technologies such as Elasticsearch and databases such as Oracle or MongoDB.
• Experience building generative AI solutions, including retrieval-augmented generation architecture, orchestration frameworks such as LangChain or LlamaIndex, and evaluation practices.
• Experience creating reusable agent skills, libraries, or patterns that accelerate delivery across engineering teams.
• Experience working across hybrid technology ecosystems using cloud services, Databricks, and Kubernetes-based platforms.

Responsibilities

• Lead the design, development, and delivery of high-quality software solutions for complex business problems using modern engineering practices.
• Drive architectural decisions and technical direction to improve the scalability, resiliency, and availability of distributed systems.
• Build and maintain secure, production-grade services and uphold code quality through reviews, testing, and engineering excellence.
• Mentor engineers through technical guidance, pairing, and actionable feedback.
• Implement continuous integration and continuous delivery automation and reliability patterns that support safe, frequent releases.
• Develop data-intensive services and workflows using Java or Scala and work with large-scale datasets and modern data platforms.
• Design and build AI-enabled applications, including retrieval-augmented generation patterns and agentic workflows, with appropriate evaluation and guardrails.
• Drive adoption of enterprise-authorized AI-assisted engineering practices to improve code quality, delivery speed, and operational outcomes; establish consistent validation standards and promote reuse of effective patterns.
• Apply knowledge of software development lifecycle tools, including authorized AI-assisted development and automation capabilities, to improve the value realized from automation.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed