Lead Software Engineer Java

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 CORPORATE TECHNOLOGY – Risk Technology 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. Drive significant business impact through your capabilities and contributions, and apply deep technical expertise and problem-solving methodologies to tackle a diverse array of challenges that span multiple technologies and applications.
Job Responsibilities
Regularly provides technical guidance and direction to support the business and its technical teams, contractors, and vendors
Develops secure and high-quality production code, and reviews and debugs code written by others
Drives adoption and governance of approved AI-assisted engineering practices across teams to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test acceleration, release readiness, incident/root-cause analysis), while establishing measurable validation standards (secure coding, peer review, automated testing) and promoting reuse of proven patterns and automation within the SDLC/TLM toolchain.
Applies knowledge of tools within the Software Development Life Cycle toolchain, including approved AI-assisted development and automation capabilities, to improve the value realized by automation at scale.
Leads team adoption of enterprise-authorized AI-assisted engineering practices and SDLC/TLM automation to improve delivery speed, quality, and operational outcomes, while setting expectations for human validation, secure handling of inputs/outputs, and consistent use of reusable patterns across teams.
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 and support capacity unlock initiatives.
Drives decisions that influence the product design, application functionality, and technical operations and processes
Serves as a function-wide subject matter expert in one or more areas of focus
Actively contributes to the engineering community as an advocate of firmwide frameworks, tools, and practices of the Software Development Life Cycle
Required qualifications, capabilities, and skills
Formal training or certification on software engineering concepts and 6+ years applied experience
Hands-on experience in system design, application development, testing, and support
Proficient in coding in Java (e.g., OOPS, Collections. Streams, Lambdas, Collections, Exception handling)
Strong knowledge of Spring Boot framework, REST API design principles and best practices
Hands-on experience with **AWS services** including Step Functions, Lambda, S3, ECS/EKS, and API Gateway, with a focus on cloud migration readiness.
Demonstrated experience leading effective use of enterprise-authorized AI-assisted software development tools within the work environment (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.
Experience leading responsible adoption of enterprise-authorized AI-assisted development and delivery tools across engineering teams, including defining ways of working (review/validation expectations), measuring outcomes, and ensuring secure handling of data.
Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, resiliency/security implications, and governance expectations; ability to coach engineers on compliant and effective usage.
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 senior engineers/leads on compliant usage patterns and controls.
Working knowledge of **AWS AI/ML and NLP services** such as Amazon SageMaker, Bedrock, Comprehend, and Textract
Experience with **Elasticsearch** for large-scale search, indexing, and analytics
Solid understanding of relational databases, SQL, CI/CD pipelines, and agile development practices.
Preferred qualifications, capabilities, and skills
Familiarity with AI/ML concepts including embeddings (Word2Vec, BERT), NLP techniques, vector search, and retrieval-augmented generation (RAG) patterns.
Exposure to additional AWS data services such as **OpenSearch, Glue, Athena, or Kinesis**.