Sr Lead Software Engineer: Customer Trust Assessment Platform

Be an integral part of an agile team that's constantly pushing the envelope to enhance, build, and deliver top-notch technology products.

As a Senior Lead Software Engineer at JPMorgan

Chase within the CONSUMER & COMMUNITY BANKING in the Fraud Technology team, you will be leading talented individuals to build Next Gen orchestration platform using advanced AI capabilities in Java & AWS.

• Provide technical guidance and direction to business and technology teams, including contractors and vendors

• Develop secure, production-grade code; review, debug, and improve code written by others

• Make and drive decisions that shape product design, application behavior, and operational processes

• Serve as a function-wide subject matter expert in one or more technical areas

• Advocate for and help teams adopt firmwide SDLC frameworks, tools, and engineering practices

• Influence peers and project stakeholders to evaluate and apply modern technologies where they provide clear value

• Promote an inclusive team culture grounded in diversity, opportunity, inclusion, and respect

• 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.

• Formal training or certification in software engineering concepts and 5+ years of applied experience in software development

• 10+ years of experience designing, developing, debugging, and maintaining applications in a large corporate environment

• Hands-on experience delivering system design, application development, testing, and operational stability

• Hands-on experience building AI agents and using AI-powered tools, including retrieval-augmented generation (RAG) pipelines and LLM APIs

• Deep knowledge in one or more technical disciplines (e.g., cloud, AI/ML), with strong understanding of modern engineering practices

• Strong hands-on experience with Java, Spring, and Spring Boot

• Experience designing and implementing REST APIs

• Strong AWS experience: ECS and Lambda, networking and core services knowledge (ALB, NLB, GWLB; VPC, subnets, security groups, IAM, Cloud Watch)

• 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

• Experience with No
  
  SQL and relational databases (e.g., Cassandra, PostgreSQL, Oracle)
• Working knowledge of Agile delivery methods and CI/CD practices
• Experience designing resilient, secure internet-facing APIs (OAuth 2.0/OIDC, JWT, TLS/mTLS, rate limiting)
• Familiarity with middleware technologies
• Experience with Infrastructure as Code (Terraform)
• Experience with observability tools (logging, metrics, tracing)
• Cloud certification