At Franklin Templeton, we’re advancing our industry forward by developing new and innovative ways to help our clients achieve their investment goals. Our dynamic firm spans asset management, wealth management, and fintech, offering many ways to help investors make progress toward their goals. Our talented teams working around the globe bring expertise that’s both broad and unique. From our welcoming, inclusive, and flexible culture to our global and diverse business, we provide opportunities to help you reach your potential while helping our clients reach theirs.

Come join us in delivering better outcomes for our clients around the world!

Role Overview

Franklin Templeton is seeking a Vice President, AI Products to drive the development and delivery of AI-powered solutions across our investment platform. This role sits at the intersection of AI, Product Management and Investment Management domain translating advanced technologies and research into scalable, production-grade capabilities.

The ideal candidate brings a strong foundation in computer science, machine learning, and quantitative finance, along with deep familiarity with investment strategies, portfolio construction, and financial markets. This individual will work closely with AI Research, AI Platform, and investment teams to bring rigor, structure, and execution discipline to AI product development.

This is a hands-on leadership role—owning product strategy and execution while actively engaging in problem-solving, model interpretation, and delivery.

Key Responsibilities:

AI Product Development & Execution

• Lead end-to-end development of AI-driven investment and other domains of analytics products, from concept through deployment

• Translate investment research and ML models into scalable, user-facing tools and workflows

• Apply strong product management rigor—defining use cases, success metrics, experimentation frameworks, and feedback loops

Partnership with AI Research & Platform

• Collaborate closely with AI Research teams to productionalize models across areas such as factor investing, portfolio optimization, and market insights

• Partner with AI Platform teams to ensure robust data pipelines, model deployment, and monitoring frameworks

• Bridge the gap between research prototypes and enterprise-grade solutions

Investment Domain Integration

• Work with business leaders, investment teams and technology partner teams to identify opportunities where AI can enhance:

  • Alpha generation and signal development

  • Portfolio construction and risk management

  • Client analytics and product innovation

• Ensure solutions are grounded in real-world investment workflows and constraints

Cross-Functional Leadership

• Drive multiple AI and technology teams to common AI product features

• Drive alignment on priorities, timelines, and measurable outcomes

• Communicate complex AI/quant concepts clearly to both technical and non-technical stakeholders

Product Strategy & Governance

• Contribute to the broader AI product roadmap aligned with business objectives

• Ensure adherence to model governance, explainability, and risk frameworks appropriate for financial services

• Promote best practices in responsible and transparent AI usage

Qualifications:

Technical & Quantitative Expertise

• Strong academic background in Computer Science, AI/ML, Quantitative Finance, or related field

• 8–15 years of experience across investment domain, AI/ML, or financial technology

• Hands-on experience with machine learning techniques and data-driven modeling

• Proficiency in programming languages such as Python, C++, or similar

Investment Experience

• Deep understanding of systematic investing, factor models, multi-asset strategies, or derivatives-based strategies

• Experience working with portfolio construction, volatility management, or risk premia strategies is highly preferred

• Familiarity with institutional and/or retail investment products (ETFs, UCITS, structured solutions)

Product & Execution Mindset

• Demonstrated ability to translate research into production-ready solutions

• Strong analytical thinking with the ability to operate in ambiguous, fas