Vice President, Full-Stack Engineer
BNY Mellon6 days ago
Pune, IndiaStaff+
Responsibilities
- Design, develop, test, deploy, and maintain full-stack applications supporting applied AI solutions and enterprise platforms.
- Integrate AI/ML capabilities, model outputs, prompts, automation workflows, data services, APIs, and enterprise systems into reliable product experiences.
- Enhance, troubleshoot, debug, upgrade, and support AI applications and platforms, including defect resolution, release support, performance improvements, and production readiness.
- Translate product requirements into technical designs, implementation plans, and maintainable working software.
- Participate in code reviews, technical documentation, automated testing, software verification, release planning, deployment, and production support.
- Apply secure coding, observability, resiliency, privacy, performance, and maintainability standards to enterprise software.
- Collaborate with product, engineering, data science, platform, operations, risk, and governance teams.
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, production support, and Agile delivery.
- 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, debugging, application reliability, communication, problem-solving, ownership, and collaboration skills.
- 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 is preferred.
- Exposure to generative AI, large language models, retrieval systems, agentic workflows, AI-assisted development, enterprise AI platforms, cloud platforms, containerization, microservices, DevOps tooling, observability, APIs, data integrations, and production support practices.
- Experience with Python, Java, JavaScript or TypeScript, React, Node.js, SQL or 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.
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