SVP, Java Full-Stack Principal Engineer - AI Hub Engineering

BNY Mellon; Florida; On-site; USD 180,000 - 290,000; Full time

Job summary

BNY is seeking a Senior Vice President, Java Full-Stack Principal Engineer to join the AI Hub Engineering team in Lake Mary, Florida. You will own end-to-end Java-based microservices delivery, set architectural guardrails, and drive reliability, security, and performance across services.

Lead a small team (5-10 engineers), shape technical direction, and collaborate with DevOps to optimize CI/CD pipelines. Experience with Java, Spring, REST, AI agents, and TDD/BDD is essential.

Qualifications

• Bachelor's degree in computer science engineering or related discipline, or equivalent work experience required.
• 9-11+ years of experience in software development required; securities/financial services exposure is a plus.
• Strong expertise in Java, Spring Framework, microservices, and Restful APIs; design patterns and architecture knowledge.

Responsibilities

• Design, build, and maintain scalable backend services using Java, Spring Boot, and REST APIs.
• Develop and consume APIs within a distributed microservices environment with focus on reliability and testability.
• Work on AI agents and LLM-based AI agents with prompt engineering; use AI platform and Python.
• Lead CI/CD pipelines via GitLab; drive SRE practices, define SLIs/SLOs, and monitor performance.

Skills

Java

Spring Framework

Microservices

REST APIs

DevOps

Education

Bachelor's degree in computer science or related field

Tools

GitLab

SLF4J/Log4j

Splunk/ELK

SonarQube

Veracode

Docker

Kubernetes

Cucumber/JUnit/Mockito

Job description

78336 Senior Vice President, Java Full-Stack Principal Engineer - Lake Mary, FL

We're seeking a future team member for the role of Senior Vice President, Full-Stack Engineer to join our AI Hub Engineering team.

This role is located in Lake Mary, FL

In this role, you'll make an impact in the following ways:

• Design and implement scalable, secure, and performant backend services using Java, Spring Boot, and REST APIs.
• Develop and consume APIs as part of a distributed microservices environment, with a focus on reliability, maintainability, and testability.
• Design, Build and test AI agents using in-house AI platform and Python to automate complex control-related tasks
• Design, develop and test LLM based AI Agents with RAG/Autogen and prompt engineering
• Implement structured logging using SLF4J and Log4j, and integrate with monitoring tools and logging aggregators (e.g., Splunk, ELK).
• Collaborate with DevOps engineers to define and optimize CI/CD pipelines using GitLab, ensuring smooth and secure build, test, and deployment workflows. Drive SRE and operational excellence: define SLIs/SLOs, instrument services (logs/metrics/traces), optimize JVM/heap/GC performance, and lead incident response to reduce MTTR.
• Apply test-driven development (TDD) and behavior-driven development (BDD) practices using Cucumber, JUnit, and Mockito.
• Ensure code quality and security by leveraging tools such as SonarQube and Veracode, with a focus on maintainable and compliant code.
• Own end-to-end delivery of Java-based microservices and platform components; set technical direction, architecture guardrails, and operational KPIs for reliability, security, and performance.
• Lead a small team (5-10 engineers), driving system-level thinking across services, data, integration, observability, and controls to achieve accelerated outcomes & Mentoring them.

To be successful in this role, we're seeking the following:

• Bachelor's degree in computer science engineering or a related discipline, or equivalent work experience required
• 9-11+ years of experience in software development required; experience in the securities or financial services industry is a plus
• Strong expertise and in depth knowledge of Java, Spring Framework (Spring MVC, Spring Boot), design patterns, Microservices architecture, and Restful APIs
• Experience in AI Code Assist Technologies (CoPilot, Claude Code, Windsurf,..)
• Strong understanding of AI agent architecture, solid grounding and prompt engineering
• Strong understanding of DevOps principles, best practice for coding and Agile development
• Proficient in automating CI/CD pipelines on large container platforms (Docker, Kubernetes)
• Batch Monitoring & Job scheduling tools like Airflow, Autosys & Control M.
• Proficient in scripting and SQL, Stored Procedures and transaction management