Lead Software Engineer - AI/Java Full Stack

We have an exciting opportunity to advance your career and drive meaningful impact by pushing the limits of modern engineering.

As a Lead Software Engineer at JPMorganChase within Corporate Technology, you will be a key technical leader within an agile team responsible for designing, building, and delivering secure, scalable, and high-performing technology solutions. You will contribute across multiple domains, partnering with business and technology stakeholders to deliver strategic platforms that enable the firm’s objectives.

Job Responsibilities

• Lead the design, development, and delivery of innovative software solutions, solving complex problems with creative and forward-thinking approaches

• Build and maintain high-quality, secure, and production-grade code, while mentoring and reviewing the work of other engineers

• Drive architecture decisions to ensure scalability, resiliency, and zero-downtime deployments

• Identify opportunities to automate operational processes and eliminate recurring issues, improving platform stability and efficiency

• Develop and implement data-intensive and statistical solutions using Java/Scala on large-scale datasets

• Design and build AI-enabled applications, including AI Agents and agentic workflows

• Work across hybrid data ecosystems (AWS, Databricks, Kubernetes)

• Ensure code quality through unit testing, integration testing, and continuous validation practices

• Collaborate with cross-functional teams to deliver end-to-end solutions aligned with enterprise standards

Required Qualifications, Capabilities, and Skills

• Significant experience in software engineering with formal training or equivalent practical expertise

• Strong proficiency in Java and Spring Boot, with working knowledge of SQL and modern front-end frameworks (e.g., React)

• Demonstrated experience in designing scalable, secure, and resilient distributed systems

• Strong understanding of modern architecture patterns (microservices, event-driven, API-first)

• Experience with CI/CD pipelines, containerization (Docker, Kubernetes/ECS/EKS), and Infrastructure as Code

• Expertise in API design (REST, GraphQL) and integration patterns

• Hands-on experience building applications on AWS or other public cloud platforms

• Experience with Generative AI systems, including:

• RAG (Retrieval-Augmented Generation) architecture

• AI orchestration frameworks (LangChain, LlamaIndex, etc.)