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Tier-1 brand and metro location increase competition, but senior specialized investor-facing AI focus narrows the candidate pool.
Deep AI system expertise combined with investment research domain expectations makes cross-industry transitions difficult.
Explicit 7+ year VP requirement plus mandatory hands-on LLM/ML, production and investor-facing experience raises shortlisting strictness.
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Design and own AI-powered research applications for portfolio management workflows, leading technical vision and end-to-end product experience.
Collaborate closely with investment researchers and portfolio managers to translate business/research needs into scalable, production-grade AI systems.
Lead lifecycle of AI applications from proof-of-concept through production, including data pipeline integration, monitoring, and observability frameworks.
Bachelor’s or Master’s degree in Computer Science, Data Science, AI/ML, or equivalent.
7+ years work experience delivering ML, AI, and data-intensive systems (for Vice President level).
Hands-on expertise in building and deploying AI systems end-to-end, including LLM workflows, prompt engineering, RAG pipelines, fine-tuning, and backend integration using Python and SQL.
Experience working directly with investors/senior partners and strong communication skills.
Experienced at partnering with investment professionals, comfortable translating complex financial research needs into AI-driven technical solutions.
Technical leader with strong product sense focused on user-centric, reliable, and safe AI applications for investment research.
Up-to-date with generative AI advancements, preferably with domain knowledge in investment management or financial services.