Lead Software Engineer - Agentic AI

Job Description

We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible.

As a Lead Software Engineer at JPMorgan

Chase with in Enterprise Technology Cloud Foundational Services, you are an integral part of an agile team that works to enhance, build, and deliver trusted, market-leading technology products in a secure, stable, and scalable way. As a core technical contributor, you are responsible for delivering critical technology solutions across multiple technical areas within various business functions in support of the firm's business objectives.

• Execute creative software solutions, design, development, and technical troubleshooting, thinking beyond routine or conventional approaches to build solutions or break down technical problems.
• Deliver end-to-end solutions in the form of cloud-native, microservices-based applications, leveraging the latest technologies and best industry practices.
• Design, develop, and deploy resilient, fault-tolerant applications on AWS, leveraging services such as ECS, EKS, Lambda, RDS, S3, and API Gateway to ensure high availability and operational excellence.
• Provision, manage, and maintain cloud infrastructure using Terraform, enforcing infrastructure-as-code best practices, reusable module design, and consistent environment management across development, staging, and production.
• Architect and build agentic AI applications using modern frameworks (e.g., Lang Chain, Lang Graph, Auto Gen, CrewAI, or AWS Bedrock Agents), enabling autonomous, multi-step reasoning and tool-use capabilities within production-grade systems.
• Identify opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems.
• Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team.
• Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation.
• Lead communities of practice across Software Engineering to drive awareness and use of new and leading-edge technologies.
• Promptly investigate and resolve issues, ensuring they do not resurface.
• Design and build scalable, secure, and reliable solutions by leveraging modern architectural patterns that ensure zero-downtime releases and optimize data performance.

• Formal training or certification on software engineering concepts and 5+ years applied experience
• Demonstrated experience leading effective use of approved AI-assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security.
• Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices
• Proficiency in back-end technologies (e.g., Python, Flask, Django) with experience building microservices-based applications; for full-stack roles, proficiency also includes front-end technologies (e.g., HTML, CSS, JavaScript, Type Script, React, Angular).
• Strong hands-on experience developing and deploying resilient applications on AWS, including deep familiarity with core AWS services, high-availability design patterns, disaster recovery strategies, and AWS Well-Architected Framework principles.
• Strong understanding and hands-on experience in cloud infrastructure provisioning using Terraform, including writing modular, reusable infrastructure-as-code, managing remote state, and integrating Terraform into CI/CD pipelines.
• Hands-on experience building agentic AI applications using one or more frameworks (e.g., Lang Chain, Lang Graph, Auto Gen, CrewAI, AWS Bedrock Agents), including designing multi-agent workflows, tool integrations, memory management, and orchestration patterns.
• Experience working with cloud platforms (e.g., AWS, Azure, GCP), distributed systems, and web technologies, including RESTful APIs and web services, Web Sockets, and JSON.
• Experience with agile development methodologies (e.g., Scrum) and an understanding of the software development life cycle..
• Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security.
• Demonstrated proficiency in software applications and technical processes within a…