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Tier-1 brand and metro location increase competition, but niche GenAI specialization limits applicant pool.
Domain-specific investor-facing AI work favors finance experience, though core ML skills remain transferable.
Explicit 7+ years and mandatory hands-on LLM/ML deployment skills create strict screening filters.
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Lead design and development of AI-powered research applications for investment workflows including Generative AI capabilities and backend integration.
Collaborate directly with investors and portfolio managers to translate research needs into scalable, production-grade AI tools and intuitive user experiences.
Own the full product lifecycle from proof of concept through production, ensuring robustness, reliability, data quality, and alignment with investor objectives.
Bachelor’s or Master’s degree in Computer Science, Data Science, AI/ML, or equivalent.
7+ years of experience delivering ML, AI, and data-intensive systems at Vice President level (3-7 years for Associate level).
Hands-on experience building and deploying AI systems end-to-end with technologies like LLM workflows, prompt engineering, RAG pipelines, entity extraction, vector search, fine-tuning, Python and SQL backend integration.
Work Experience Required: 7+ years (VP level) or 3-7 years (Associate level); Notice period: Not explicitly mentioned in the JD.
Strong technical leadership in applying generative AI and advanced AI/ML technologies in production for investment research applications.
Experience working directly with senior investment stakeholders to translate complex research workflows into AI-driven products with strong product intuition and user-centric design.
Domain knowledge or familiarity with investment management, financial services, and asset classes is a differentiator.