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Metro location, popular AI title, broad full-stack/LLM requirements, and reputable firm increase competition.
Core ML/AI skills are transferable across industries, but finance domain experience is preferred, so medium sensitivity.
Many mandatory technical skills (LLMs, RAG, vector DBs, cloud, full-stack) indicate high filtration.
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Develop and deploy AI-powered applications integrated with large language models (LLMs) to enhance investment management workflows and generate actionable insights.
Engineer scalable technology stacks focused on generative AI adoption across asset management functions including distribution, investments, and investment operations.
Collaborate cross-functionally with global teams to design automated workflows and integrate AI solutions meeting performance, security, and compliance standards.
Bachelor's or Master's degree in Computer Science, Data Science, Statistics, or related field.
Strong software engineering skills with hands-on development experience, especially advanced Python programming and generative AI techniques (prompt engineering, fine tuning, RAG architecture).
Experience with cloud computing (AWS), containerization, version control (Git), CI/CD pipelines, and full-stack development including React/JavaScript and RESTful APIs.
Work Experience Required: Not explicitly mentioned in the JD.
Engineering (B.E./B.Tech.) or Master's (Statistics, Quant, Mathematics) degree from a well-recognized institute.
Demonstrated ability to translate complex business needs into technical AI-driven solutions in agile, fast-paced, globally distributed environments.
Experience or interest in financial services or investment management along with technical expertise in large-scale data handling and AI automation workflows.