Senior Vice President, Forward Deployed Engineer

BNY Mellon•New York, NY

About The Position

In this role, you'll make an impact by embedding with business and platform stakeholders to scope and execute time-boxed FDE engagements with clear entry and exit criteria, translating defined opportunities into production-ready delivery plans. You will design, build, and harden AI-first solutions across data, APIs, services, and workflow integrations, moving confidently from prototype to secure, scalable production deployment. The role emphasizes a reuse-first delivery approach, extending existing platforms, templates, and modules rather than building avoidable one-offs, and contributing reusable code and patterns back to shared repositories. You will execute discovery with operating teams and sponsors to clarify constraints, validate feasibility, and rapidly prototype where useful before hardening into production. Additionally, you will surface patterns and learnings from engagements that can be standardized and promoted into shared platform capabilities, apply secure-by-default practices consistently, and incorporate observability, testability, and operational readiness into every solution delivered. You will prepare clear handoff packages and transition plans so owning teams can sustain solutions independently after forward deployment ends. Operating within the FDE playbook, you will contribute feedback to refine standards, handoff criteria, and working norms based on field experience. You will coordinate with control, architecture, security, and compliance stakeholders to keep solutions production-appropriate and governance-compliant. You will program well-designed, testable, efficient code, actively participate in code reviews, and maintain software functionality while managing technical debt. You will apply security and privacy principles throughout the software development lifecycle and mentor junior engineers, engage in active learning, complete mandatory training, and stay abreast of emerging technologies.

Requirements

Bachelor's degree in computer science, engineering, or a related discipline, or equivalent work experience.
10–14 years of hands-on software development experience, including direct delivery of production systems; experience in the securities or financial services industry is a plus.
Strong foundational understanding of modern AI and agentic application patterns, including retrieval-augmented generation (RAG), semantic search, and agent-based system design.
Hands-on experience building backend services, APIs, and production systems.
Experience working across architecture, data, and platform concerns rather than only within a narrow layer.
Strong software engineering skills in one or more of: Java, TypeScript/JavaScript, Python.
Experience with APIs, service integration, and secure-by-default engineering practices.
Ability to work across data, AI, workflow, and platform layers as needed.
Comfort using modern AI tooling pragmatically without confusing prototypes for production systems.
Familiarity with application frameworks and containerization.
Strong written and verbal communication across technical and non-technical audiences.
Clear product and delivery judgment within a scoped engagement.
Ability to coordinate and execute across stakeholders without formal authority.
Practical tradeoff thinking under real constraints.
Bias toward action with disciplined follow-through.
Mentors junior engineers within engagements; contributes to team delivery quality and knowledge sharing.

Nice To Haves

Experience delivering AI, data, or workflow-heavy solutions in regulated environments.
Strong systems-thinking and architecture judgment across services, data, and infrastructure.
Comfort operating in ambiguity and driving discovery with senior stakeholders.
Experience balancing speed with governance, security, and operational rigor.
Familiarity with reusable platform patterns, internal developer platforms, or productized infrastructure.
Experience with observability, evaluation, and day-2 production ownership practices.

Responsibilities

Embed with business and platform stakeholders to scope and execute time-boxed FDE engagements with clear entry and exit criteria; translate defined opportunities into production-ready delivery plans.
Design, build, and harden AI-first solutions across data, APIs, services, and workflow integrations, moving confidently from prototype to secure, scalable production deployment.
Default to reuse-first delivery: extend existing platforms, templates, and modules rather than building avoidable one-offs; contribute reusable code and patterns back to shared repositories.
Execute discovery with operating teams and sponsors to clarify constraints, validate feasibility, and rapidly prototype where useful before hardening into production.
Surface patterns and learnings from engagements that can be standardized and promoted into shared platform capabilities.
Apply secure-by-default practices consistently; incorporate observability, testability, and operational readiness into every solution delivered.
Prepare clear handoff packages and transition plans so owning teams can sustain solutions independently after forward deployment ends.
Operate within the FDE playbook and contribute feedback to refine standards, handoff criteria, and working norms based on field experience.
Coordinate with control, architecture, security, and compliance stakeholders to keep solutions production-appropriate and governance-compliant.
Program well-designed, testable, efficient code; actively participate in code reviews and maintain software functionality while managing technical debt.
Apply security and privacy principles throughout the software development lifecycle.
Mentor junior engineers; engage in active learning, complete mandatory training, and stay abreast of emerging technologies.