Lead Software Engineer Java Spring boor Gen AI
JPMorgan Chase & Co.Match Score
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Protocol Intelligence
Data-driven signals on your job's competitivenessStrong Tier-1 brand and broad backend/GenAI requirements increase applicant competition moderately.
Enterprise banking, regulated controls, and AI production focus reduce cross-industry transferability.
Mandatory 9+ years, Java/Spring, Python, distributed systems, and ML production experience enforce strict screening.
Job Description
Structured overview of role & requirementsAbout This Role
Own end-to-end solution architecture, including applications, APIs, data, integrations, and environments from development to production.
Lead hands-on technical development in Java/Spring Boot and Python, including reference implementations, POCs, design spikes, and complex production issue resolution.
Design and deliver production patterns for AI/ML capabilities and partner with Data Science teams to operationalize machine learning models with responsible AI controls.
Minimum Requirements
9+ years of applied experience with formal training or certification in software engineering concepts.
Strong expertise in Java 11/17+, Spring Boot microservices, Python 3.x, API design, testing, and distributed systems involving microservices and event-driven architectures using tools like Kafka.
Practical experience in productionizing AI/ML services including inference patterns, model packaging, monitoring, MLOps, and delivery with DevOps tools such as CI/CD and automated testing.
Experience in secure and resilient software development suitable for regulated environments, including operational excellence with NFRs like availability, latency, scalability, and compliance.
Ideal Candidate Profile
Senior software engineer with demonstrated ownership of enterprise-grade end-to-end architecture and hands-on delivery in Java/Spring Boot and Python.
Experience working in regulated, security-conscious environments with a strong focus on operational rigor, production readiness, and observability.
Proven ability to integrate AI/ML models into scalable, reliable services, and implement responsible AI governance and operational frameworks.