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Tier-1 brand, metro location, mid-level generalist GenAI role with broad skillset increases candidate competition.
Requires deep GenAI and MLOps expertise, favoring candidates with financial-services analytics experience.
Explicit 5–8 years and mandatory GenAI, MLOps, and ML skills enforce strict shortlisting.
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Lead end-to-end design, implementation, testing, deployment, and support of AI-powered products focusing on generative AI and deep learning solutions.
Analyze diverse data sources including unstructured data (emails, call transcripts) and structured transaction/client data to derive insights that improve client experience and business outcomes.
Collaborate cross-functionally to identify strategic business priorities, apply GenAI techniques (prompt engineering, RAG, fine-tuning), and translate ambiguous problems into actionable AI solutions.
5 to 8 years of relevant experience in Data Science, with at least 2 years focused on Generative AI solutions.
Experience deploying AI/ML products in production within an agile environment, preferably in financial services.
Proficiency with LLMs, transformer architectures, prompt engineering, RAG (embeddings, vector indexes), model customization techniques, and the PyTorch/TensorFlow and Hugging Face ecosystems.
Master's degree preferred in Computer Science or Engineering; no explicit mention of mandatory notice period or location requirements.
Experienced in tackling client experience and operations business problems specifically in financial services with analytical and AI solutions.
Able to operate independently on complex problems, applying in-depth AI domain knowledge combined with data analysis and software engineering skills.
Comfortable working in ambiguous situations requiring curiosity and translating business problems into scalable AI products with documentation and risk/compliance considerations.