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 JPMorganChase within the CONSUMER & COMMUNITY BANKING in the Fraud Technology team, you will be leading talented individuals to build NextGen orchestration platform using advanced AI capabilities in Java & AWS.
Job responsibilities
- 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.
Required qualifications, capabilities, and skills
- 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, CloudWatch)
- 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
Preferred qualifications, capabilities, and skills
- Experience with NoSQL 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