Vice President, Full-Stack Engineer
BNY Mellon5 days ago
Pune, IndiaStaff+
Responsibilities
- Design, develop, test, deploy, and maintain full-stack applications supporting applied AI solutions, enterprise platforms, and AI-enabled product flows.
- Integrate AI/ML capabilities, model outputs, prompts, automation workflows, data services, APIs, and enterprise systems into reliable product experiences.
- Enhance, troubleshoot, upgrade, and support AI platforms and existing systems, including defect resolution, release support, performance improvements, and technical debt reduction.
- Translate product requirements into technical designs, implementation plans, and maintainable working software with product, engineering, data science, and platform teams.
- Participate in code reviews, technical documentation, automated testing, release planning, deployment, production readiness, debugging, and performance tuning.
- Ensure solutions meet enterprise standards for security, privacy, resiliency, observability, architecture, and change management.
- Collaborate with product, engineering, data science, platform, operations, risk, and governance teams to deliver AI-enabled capabilities.
Requirements
- 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, 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 reviewing logs, resolving defects, and improving application reliability.
- Understanding of security, privacy, performance, resiliency, and maintainability in enterprise software development.
- Bachelor’s degree in computer science, engineering, or a related discipline, or equivalent work experience.
- 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, and NoSQL databases.
- Familiarity with AI observability, workflow automation, prompt orchestration, model lifecycle tooling, or data pipeline integration is a plus.
Categories