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Strong Tier-1 brand and metro locations increase competition, but seniority and niche specialization reduce applicant density.
Role requires specialized LLM, safety, and finance-regulatory experience, limiting cross-industry transferability.
Explicit 12+ years requirement and advanced ML/AI, safety, and compliance expertise make shortlisting highly strict.
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Lead research and deployment of large language model (LLM)-based AI agents handling multi-step workflows, tool usage, and multi-agent coordination.
Manage end-to-end lifecycle of AI agents from research direction to production systems addressing latency, accuracy, compliance, and safety in a regulated financial domain.
Collaborate with cross-functional teams (Product, Engineering, Design, Risk) to bring AI systems to market, defining and tracking success metrics like task completion, accuracy, latency, and customer satisfaction.
Ph.D. with 8+ years or M.S. with 12+ years experience building and deploying AI systems in production.
Applied experience with generative AI LLMs including fine-tuning, prompt engineering, and retrieval-augmented generation (RAG).
Experience scaling LLM systems with caching, batching, governance, and evaluation frameworks.
Proficiency in Python and machine learning frameworks such as PyTorch, TensorFlow, Hugging Face, and scikit-learn.
Strong foundation in machine learning, deep learning, statistical modeling, experimental design, and information retrieval or recommendation systems.
Proven ability to set technical research agendas and drive projects from concept through production deployment with measurable outcomes.
Experience leading conversational AI, multi-agent orchestration, reinforcement learning or preference optimization, with emphasis on safety, governance, and regulatory compliance.