Lead Software Engineer - AI/Java Full Stack

Job description

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.) LLM evaluation frameworks and responsible AI practices (guardrails, content filtering) Preferred Qualifications, Capabilities, and Skills Deep expertise in Java, object-oriented design, and system design Experience with ElasticSearch, Oracle, MongoDB, and modern data platforms
• Proven experience building AI-enabled applications and agentic architecture Experience developing reusable AI Agent skills/frameworks to accelerate engineering teams.