Senior Director, Engineering Group Lead

BNY Mellon•New York, NY

2d•Onsite

About The Position

We’re seeking a future team member for the role of Senior Director, Engineering Group Leader to join our Enterprise Onboarding team. This role is located in Pittsburgh, PA, New York, NY or Jersey City, NJ. In this role, you’ll make an impact in the following ways: Lead the design, development, testing, and deployment of scalable, secure, reliable, and maintainable software solutions Serve as a hands-on engineer and contribute directly to architecture, coding, troubleshooting, code reviews, testing, documentation, and release management. Lead and develop a small, high-performing global engineering team with a focus on execution, inclusion, collaboration, and technical excellence. Drive disciplined practices across the Software Development Life Cycle (SDLC), Product Development Life Cycle (PDLC), Agile delivery, and product operating model. Partner with product, engineering, and business stakeholders to translate needs into well-designed technical solutions and executable delivery plans. Champion AI-enabled software development tools and practices to improve engineering productivity, quality, and speed. Balance strategic objectives with day-to-day delivery, planning, prioritization, and issue resolution. Coach and mentor engineers while building technical capability and a culture of continuous learning.

Requirements

Bachelor's degree in a related discipline or equivalent work experience required.
Applicable local/regional licenses or certifications as required by the business
12-15 years of total work experience
At least five years of software engineering experience, including demonstrated success as a hands-on developer with strong technical depth.
Strong experience designing and delivering enterprise software, platform and AI solutions in complex environments.
Deep understanding of AI engineering patterns, preferably with a background in Machine Learning (deep learning ideal)
Hands-on knowledge of AI/ML architecture across training, inference, feature pipelines, model serving, orchestration, agent protocols, etc.
Strong platform engineering skills across APIs, microservices, cloud infrastructure, CI/CD, observability, and secure deployment.
Experience working with AI platforms, developer platforms, or internal enablement products.
Ability to translate complex technical concepts into clear architecture decisions, delivery plans, and business outcomes, and ability to spot flaws and risks in designs.
Strong knowledge of Agile delivery, product operating model practices, SDLC, and PDLC frameworks.
Experience applying AI-enabled software development tools, workflows, and engineering productivity practices.
Strong communication, collaboration, problem-solving, and stakeholder-management skills.
Proven ability to deliver effectively in a dynamic, outcome-focused environment.

Nice To Haves

at least 3-5 years of management experience preferred.
Applied AI, ML/optimization, orchestration and software architecture, including evaluation frameworks and guardrail design
Vector databases, retrieval systems, knowledge graphs, memory-based agents and agentic protocols
MLOps, model lifecycle tooling, and production AI observability
Experience with AI for engineering practices and agentic SDLC design, with an eye toward production scale and resilience

Responsibilities

Lead the design, development, testing, and deployment of scalable, secure, reliable, and maintainable software solutions
Serve as a hands-on engineer and contribute directly to architecture, coding, troubleshooting, code reviews, testing, documentation, and release management.
Lead and develop a small, high-performing global engineering team with a focus on execution, inclusion, collaboration, and technical excellence.
Drive disciplined practices across the Software Development Life Cycle (SDLC), Product Development Life Cycle (PDLC), Agile delivery, and product operating model.
Partner with product, engineering, and business stakeholders to translate needs into well-designed technical solutions and executable delivery plans.
Champion AI-enabled software development tools and practices to improve engineering productivity, quality, and speed.
Balance strategic objectives with day-to-day delivery, planning, prioritization, and issue resolution.
Coach and mentor engineers while building technical capability and a culture of continuous learning.
Lead solution architecture for frontier AI products and identify key business applications within Eliza Frontier Solutions.
Review and refine end-to-end technical designs for AI applications and agentic workflows, with a focus on reusability, resilience, observability and commercial viability.