Lead Software Engineer - Java, AI, React
Lead Software Engineer - Java, AI, React
JP Morgan Chase & Co.Early Applicant
- Posted a month ago
- Be among the first 30 applicants
Job Description
We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible.
As a Lead Software Engineer at JPMorgan Chase within the Corporate Technology line of business, 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.
Job responsibilities
As a Lead Software Engineer at JPMorgan Chase within the Corporate Technology line of business, 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.
Job responsibilities
- Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or breakdown technical problems
- Develops secure and high-quality production code, and reviews and debugs code written by others
- 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.
- 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.
- 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.
- Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems
Leads evaluation sessions with external vendors, startups, and internal teams to drive outcomes-oriented probing of architectural designs, technical credentials, and applicability for use within existing systems and information architecture
Required qualifications, capabilities, and skills
- Formal training or certification on software engineering concepts and 12+ years applied experience
- Hands-on practical experience delivering system design, application development, testing, and operational stability
- Advanced in one or more programming language(s) Java, Sprint Boot, React JS, AI/ML
- 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
- Proficient in all aspects of the Software Development Life Cycle
- 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.
- Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
- In-depth knowledge of the financial services industry and their IT systems
- Practical cloud native experience
Preferred qualifications, capabilities, and skills
- Certification is preferred in AI /Java/ React
More Info
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Function:
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Key Skills
About Company
Skills:
Java, Graphql, Spring Boot, API design, Sql, React, REST, Docker, ECS, Databricks, Kubernetes, AWS, LangChain, AI orchestration frameworks, Infrastructure as Code, EKS, Generative AI systems, CI/CD pipelines, LLM evaluation frameworks, LlamaIndex
Skills:
secure coding , Performance Tuning, Spring Boot, Grafana, Angular, Microservices, React, Dynatrace, Splunk, AWS, Test strategy automation, Incident root-cause analysis, CI/CD strategy and execution, Resilient highly available architectures, Observability and monitoring, AI-assisted software development tools, SQL databases, Kafka event-driven architecture
Skills:
secure coding , Performance Tuning, Spring Boot, Grafana, Angular, Microservices, Automated Testing, React, Dynatrace, Splunk, Data Modelling, Query Optimization, AWS, Test strategy automation, Incident root-cause analysis, CI/CD strategy and execution, Observability and monitoring, AI-assisted software development tools, SQL databases, Kafka event-driven architecture
Skills:
Java, Azure ML, Spring Batch, Gradle, Maven, Restful Apis, LangChain4j, GitHub Actions, Azure OpenAI Service, Spring AI, Quarkus
Skills:
Large Language Models (LLMs), Machine Learning, Apis, Sql, Microservices, Data Science, MLops, Terraform, Python, AWS, Generative AI, LLMOps, NoSQL databases, Agentic AI systems, Prompt Engineering, Containerized deployments