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BNY

Senior Vice President, AI / Machine Learning Software Engineer

Posted 12 Days Ago
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In-Office
Pune, Mahārāshtra, IND
Senior level
In-Office
Pune, Mahārāshtra, IND
Senior level
Lead AI strategy and delivery across Asset Servicing and Middle Office: identify and prioritize AI use cases, design and implement production-grade AI/ML and generative AI solutions, ensure scalability, security, governance, and operational support, partner with cross-functional stakeholders, evaluate value and risk, and mentor teams to accelerate responsible AI adoption and measurable business outcomes.
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We are seeking a Senior Vice President, AI Engineer with deep Asset Servicing and Middle Office domain knowledge to help drive an AI-first mindset across the organization. This role will identify high-value opportunities to apply AI, partner with business and technology stakeholders to shape strategy, and lead the design and delivery of scalable AI-enabled solutions that improve client experience, operational efficiency, risk management, and decision-making.

The ideal candidate combines strong technical depth in AI/ML and modern engineering with a practical understanding of Asset Servicing and Middle Office workflows, data, controls, and operating models. This individual will translate business problems into AI use cases, guide solution architecture, and help accelerate responsible adoption of AI capabilities across the platform.

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

  • Partner with business, product, operations, and engineering leaders to identify, prioritize, and define AI use cases across Asset Servicing and Middle Office.
  • Apply an AI-first lens to business processes, client journeys, and operational workflows to uncover opportunities for automation, insight generation, decision support, and productivity improvement.
  • Design, build, and help implement AI/ML and generative AI solutions, including prototypes, production-ready services, and reusable patterns.
  • Translate domain needs into technical requirements, solution designs, and delivery roadmaps aligned to platform and business priorities.
  • Work closely with data, architecture, security, risk, and engineering teams to ensure solutions are scalable, secure, well-governed, and operationally supportable.
  • Evaluate feasibility, value, and risk of AI opportunities, including data readiness, model suitability, controls, and adoption considerations.
  • Establish and promote engineering standards, design patterns, and best practices for responsible AI development and deployment.
  • Support experimentation and innovation while maintaining strong focus on business outcomes, control requirements, and production quality.
  • Communicate solution approach, trade-offs, and business value clearly to both technical and non-technical stakeholders.
  • Mentor engineers and cross-functional teams on AI capabilities, domain-driven problem solving, and practical application of emerging technologies.

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

  • Bachelor’s degree in Computer Science, Engineering, Data Science, or related field, or equivalent practical experience.
  • Significant experience in software engineering, AI/ML engineering, or applied data/AI solution delivery.
  • Strong domain knowledge of Asset Servicing and Middle Office, including business processes, data flows, operational controls, and client/service considerations.
  • Experience identifying business problems and translating them into AI/ML, analytics, or generative AI solutions.
  • Hands-on experience designing and building production-grade solutions using modern engineering practices, APIs, cloud-native services, and data platforms.
  • Strong understanding of AI/ML lifecycle concepts, including model development, evaluation, deployment, monitoring, and governance.
  • Experience working across cross-functional teams to deliver complex initiatives from concept through implementation.
  • Strong communication and stakeholder management skills, with ability to influence across business and technology organizations.
  • Demonstrated ability to balance innovation with risk, governance, and regulatory expectations in a financial services environment.

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