Senior Lead Software Engineer - Java/Kafka/AWS

JPMorgan Chase & Co.; Jersey City (NJ); Presencial; USD 150 000 - 190 000; Tempo integral

Resumo da oferta

JPMorgan Chase & Co. in Jersey City seeks a Senior Lead Software Engineer to advance Java/Kafka/AWS based solutions within an agile Digital Utilities team.

You will drive design decisions, mentor engineers, and promote AI-assisted coding practices with a focus on security, reliability, and scalable delivery.

Qualificações

• Formal training or certification in software engineering with 5+ years of hands-on experience.
• Experience delivering system design, application development, testing, and operational stability.
• Proficiency in Java, Springboot, Microservices, API, Kafka, Cassandra, AWS and AI tools.
• Experience using enterprise AI-assisted development tools and setting team expectations for AI outputs.
• Knowledge of secure coding practices and responsible AI usage in workflows.

Responsabilidades

• Provides technical guidance to business teams, contractors, and vendors.
• Develops secure, high-quality production code and reviews peers' work.
• Drives adoption of AI-assisted engineering practices across teams with governance and standards.
• Improves value from automation in the SDLC/TLM toolchain.
• Applies SDLC toolchain knowledge to enhance automation and outcomes.
• Influences product design, functionality, and technical operations decisions.
• Acts as a subject matter expert across key engineering areas.

Conhecimentos

Java

Springboot

Microservices

API

Kafka

Cassandra

AWS

AI

Descrição da oferta de emprego

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 - Java/Kafka/AWS at JPMorganChase within the Digital Utilities team, 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.
• 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 5+ years applied experience
• Hands-on practical experience delivering system design, application development, testing, and operational stability
• Advanced in one or more programming language(s) including Java, Springboot, Microservices, API, Kafka, Cassandra, AWS and AI.
• 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
• 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.
• Ability to tackle design and functionality problems independently with little to no oversight
• Practical cloud native experience

Preferred qualifications, capabilities, and skills

• Modern emerging technologies