Senior Vice President, Engineering Group Leader

BNY Mellon•Lake Mary, FL

4h•Onsite

About The Position

We’re seeking a future team member for the role of Senior Vice President, Application Development Manager to join our Enterprise Data & Solutions Engineering team. This role is located in Lake Mary, Florida. This is a hands-on leadership role for an experienced application development manager who can provide technical direction, actively contribute to solution design and engineering delivery, and lead a small team of engineers building modern Java-based, AI-enabled enterprise platforms.

Requirements

Bachelor’s degree in computer science, engineering, or a related discipline, or equivalent work experience required.
10+ years of software development experience, including significant hands-on experience with enterprise application development; experience in securities, banking, or financial services is a plus.
Prior experience leading or managing engineering teams, preferably small to mid-sized teams of 5–10 engineers, with demonstrated ability to mentor, guide, and deliver through others while remaining technically hands-on.
Strong expertise in Java, Spring Framework, Spring MVC, Spring Boot, design patterns, microservices architecture, and RESTful APIs.
Strong understanding of AI agent architecture, LLM-based application patterns, RAG, prompt engineering, grounding, evaluation, and responsible AI considerations.
Experience with AI code-assist technologies such as GitHub Copilot, Claude Code, Windsurf, or similar developer productivity tools.
Strong understanding of DevOps principles, secure coding practices, Agile delivery, CI/CD automation, and modern engineering best practices.
Proficiency in building and automating CI/CD pipelines on large-scale container platforms using Docker, Kubernetes, GitLab, or equivalent tools.
Experience with observability, production support, SRE practices, incident management, performance tuning, and operational resilience.
Experience with batch monitoring and job scheduling tools such as Airflow, Autosys, Control-M, or equivalent platforms.
Proficiency in scripting, SQL, stored procedures, transaction management, and integration with enterprise data platforms.
Strong knowledge of code quality and application security tools such as SonarQube, Veracode, dependency scanning, and secure SDLC practices.
Ability to set technical direction, influence architecture decisions, manage delivery priorities, and communicate effectively with senior stakeholders, business partners, architects, and engineering teams.
Demonstrated ability to balance hands-on engineering contribution with leadership responsibilities, including planning, mentoring, delivery management, and production accountability.
Strong analytical, problem-solving, collaboration, and communication skills, with a passion for building high-quality, resilient, and AI-enabled enterprise solutions.

Responsibilities

Lead the design, development, and delivery of scalable, secure, and performant backend services using Java, Spring Boot, REST APIs, and microservices architecture.
Serve as a hands-on technical leader, contributing to architecture, design reviews, code reviews, complex problem-solving, and delivery of critical platform capabilities.
Manage, mentor, and coach a small team of 5–10 engineers, providing technical direction, delivery oversight, prioritization, and career development support.
Own end-to-end delivery across the software development lifecycle, from requirements and design through development, testing, deployment, production support, and continuous improvement.
Design, build, and test AI agents and LLM-based AI solutions using in-house AI platforms, Python, RAG, prompt engineering, and agentic frameworks.
Drive adoption of AI code-assist technologies such as GitHub Copilot, Claude Code, Windsurf, or similar tools to improve productivity, quality, and delivery speed.
Define technical direction, architecture guardrails, reusable patterns, and operational KPIs for reliability, security, scalability, performance, and maintainability.
Partner with DevOps, SRE, architecture, product, and business stakeholders to optimize CI/CD pipelines, observability, incident response, and operational resilience.
Implement structured logging using SLF4J and Log4j, and integrate applications with enterprise monitoring and logging platforms such as Splunk, ELK, or equivalent tools.
Apply test-driven development and behavior-driven development practices using JUnit, Mockito, Cucumber, and related testing frameworks.
Ensure engineering quality, security, and compliance through automated testing, TDD/BDD practices, SonarQube, Veracode, secure coding, and peer review.
Lead system-level thinking across services, data, integration, observability, controls, and operational workflows to deliver sustainable, business-aligned solutions.
Foster a culture of engineering excellence, accountability, innovation, inclusion, continuous learning, and hands-on problem solving.