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Hybrid remote, broad generative AI and full-stack requirements, and a popular senior ML title drive high competition.
Core ML/AI skills are transferable, but asset-management preference increases industry specificity.
Multiple mandatory technical skills (LLMs, RAG, vector DBs, cloud, full-stack) increase screening strictness.
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Design, develop, and deploy AI-enabled production applications integrated with Large Language Models (LLMs) to improve investment management workflows and generate insights.
Build scalable, automated workflows and solutions across distribution, investments, and investment operations using generative AI technologies including RAG architectures and vector databases.
Collaborate cross-functionally with global teams to deliver AI-powered analytics and optimize existing investment processes ensuring performance, security, and compliance.
Bachelor's or Master's degree in Computer Science, Data Science, Statistics, or related field required.
Advanced Python programming and experience with generative AI models including prompt engineering, fine tuning, and retrieval-augmented generation (RAG).
Proficiency with cloud computing (AWS), containerization, version control (Git), CI/CD pipelines, and full-stack development (React/JavaScript, RESTful APIs).
Work Experience Required: Not explicitly mentioned in the JD.
Engineering (B.E./B.Tech) graduate or Masters in Statistics, Quantitative disciplines from recognized institute with strong software engineering fundamentals.
Experience or interest in financial services or investment management domain is preferred.
Able to work effectively in fast-paced, agile, globally distributed teams; strong technical communication skills with ability to translate business needs into technical AI solutions.