Senior Specialist, Full-Stack Engineer

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

• Design, develop, test, deploy, and maintain full stack applications that support applied AI solutions, enterprise platform capabilities, and AI-enabled product flows.
• The Vice President, Full Stack AI Developer will work closely with product managers, product owners, engineering leads, data scientists, platform teams, and governance partners to translate product needs into high-quality technical solutions. The role requires strong engineering fundamentals, practical AI fluency, disciplined execution, and the ability to contribute across solution delivery, integration, testing, deployment, production readiness, and ongoing platform support.
• Support applied AI solution delivery by integrating AI/ML capabilities, model outputs, prompts, automation workflows, data services, APIs, and enterprise systems into reliable product experiences.
• Provide platform support for AI capabilities, including enhancements, defect resolution, release support, troubleshooting, performance improvements, and maintainability.
• Support AI product enhancement across platforms by improving existing workflows, adding new capabilities, integrating reusable components, and ensuring solutions scale across business and technology environments.
• Partner with product owners, product managers, data scientists, and engineering teams to translate requirements into clear technical designs, implementation plans, and working software.
• Develop well-designed, testable, efficient, and maintainable code to solve business and technology problems.
• Participate in solution design, code reviews, technical documentation, testing, release planning, deployment activities, and production readiness.
• Support application quality through automated testing, software verification, debugging, performance tuning, and secure coding practices.
• Troubleshoot, debug, upgrade, and enhance existing systems while managing technical debt and improving software maintainability.
• Ensure software solutions are aligned to enterprise architecture, security, privacy, resiliency, observability, and change management standards.
• Leverage existing products, reusable components, and platform capabilities to improve engineering efficiency and avoid duplication.
• Collaborate across product, engineering, data science, platform, operations, risk, and governance teams to deliver high-quality AI-enabled capabilities.

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

• Preferred 10+ years of experience in software development, full stack engineering, application development, platform support, or related technology roles.
• Experience developing, supporting, and enhancing enterprise applications using modern application, API, integration, and platform technologies.
• Strong understanding of software development lifecycle practices, Agile delivery, CI/CD, automated testing, code reviews, release management, and production support.
• Experience building secure, scalable, testable, and maintainable software in complex enterprise environments.
• Familiarity with AI-enabled applications, automation platforms, data-driven products, model integrations, prompt-based workflows, or AI/ML-enabled software solutions.
• Strong troubleshooting skills, including debugging application behavior, reviewing logs, resolving defects, and improving application reliability.
• Understanding of security, privacy, performance, resiliency, and maintainability considerations in enterprise software development.
• Ability to work effectively with product, engineering, data science, platform, operations, risk, and governance teams.
• Strong communication, problem-solving, ownership, and collaboration skills.
• Bachelor’s degree in computer science, Engineering, or a related discipline, or equivalent work experience required.
• Experience in financial services, enterprise technology, or another highly regulated environment.
• Exposure to generative AI, large language models, retrieval systems, agentic workflows, AI-assisted development, or enterprise AI platforms.
• Experience with cloud platforms, containerization, microservices, DevOps tooling, observability, APIs, data integrations, and production support practices.
• Experience with Python, Java, JavaScript / TypeScript, React, Node.js, SQL / NoSQL databases, APIs, and modern engineering toolchains.
• Familiarity with AI observability, workflow automation, prompt orchestration, model lifecycle tooling, or data pipeline integration is a plus.