Director, Full-Stack Engineer

BNY Mellon•Lake Mary, FL

3d•Onsite

About The Position

We’re seeking a future team member for the role of Director Vice President, Full-Stack Engineer to join our AI Engineering team. In this role, you’ll make an impact by designing and implementing scalable, secure, and performant backend services using Java, Spring Boot, and REST APIs. You will develop and consume APIs as part of a distributed microservices environment, with a focus on reliability, maintainability, and testability. You will also design, build, and test AI agents using an in-house AI platform and Python to automate complex control-related tasks, and design, develop, and test LLM based AI Agents with RAG/Autogen and prompt engineering. You will implement structured logging using SLF4J and Log4j, and integrate with monitoring tools and logging aggregators (e.g., Splunk, ELK). You will collaborate with DevOps engineers to define and optimize CI/CD pipelines using GitLab, ensuring smooth and secure build, test, and deployment workflows. You will drive SRE and operational excellence by defining SLIs/SLOs, instrumenting services (logs/metrics/traces), optimizing JVM/heap/GC performance, and leading incident response to reduce MTTR. You will apply test-driven development (TDD) and behavior-driven development (BDD) practices using Cucumber, JUnit, and Mockito. You will ensure code quality and security by leveraging tools such as SonarQube and Veracode, with a focus on maintainable and compliant code. You will 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. You will lead a small team (5–10 engineers), driving system-level thinking across services, data, integration, observability, and controls to achieve accelerated outcomes & Mentoring them.

Requirements

Bachelor's degree in computer science engineering or a related discipline, or equivalent work experience required
12+ years of experience in software development required
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

Nice To Haves

experience in the securities or financial services industry is a plus

Responsibilities

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.