Specialist, Full-Stack Engineer

Role overview

Specialist, Full-Stack Engineer at BNY Mellon

We’re seeking a future team member for the role of Specialist, Full-Stack Engineer to join our DATA SOLUTIONS AND SVCS PLATFORM team.

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.

Responsibilities

• 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.
• 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.
• Develop well-designed, testable, efficient, and maintainable code to solve business and technology problems.
• Collaborate across product, engineering, data science, platform, operations, risk, and governance teams to deliver high-quality AI-enabled capabilities.

Required qualifications

• Bachelor’s degree in computer science, Engineering, or a related discipline, or equivalent work experience required.

Preferred qualifications and skills

• To be successful in this role, we’re seeking the following: Preferred 3+ years of experience in software development, full stack engineering, application development, platform support, or related technology roles.

Employment details

• Location: Pune [Mh] [India]

Application details

• Support application quality through automated testing, software verification, debugging, performance tuning, and secure coding practices.
• Experience developing, supporting, and enhancing enterprise applications using modern application, API, integration, and platform technologies.

Additional role details

• This role is located in Pune.
• 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.
• Provide platform support for AI capabilities, including enhancements, defect resolution, release support, troubleshooting, performance improvements, and maintainability.
• Partner with product owners, product managers, data scientists, and engineering teams to translate requirements into clear technical designs, implementation plans, and working software.
• Participate in solution design, code reviews, technical documentation, testing, release planning, deployment activities, and production readiness.
• 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.
• 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.
• 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.