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Senior, niche LLM role at a Tier-1 bank increases selectivity despite strong employer visibility.
Core LLM engineering skills transferable, but regulated finance/KYC context requires domain familiarity.
Explicit 10+ years, leadership, and specialist LLM, RAG, and fine-tuning requirements raise screening strictness.
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Own technical vision and delivery of AI/ML prompt engineering and model development team (8–15 members) focused on KYC/AML intelligent document processing.
Architect and operationalize multi-step AI workflows including prompt lifecycle management, evaluation frameworks, and model selection/optimization balancing accuracy, latency, and cost.
Partner cross-functionally to ensure compliance, model risk governance, and data pipeline robustness while leading iterative improvements under ambiguity.
10+ years experience in NLP/AI/ML or computational linguistics, including 3+ years leading technical teams with direct reports.
Hands-on expertise in LLM internals, prompt architecture design/debugging, RAG system design, fine-tuning methodologies, and ML engineering (Python, PyTorch, Hugging Face, LangChain/LlamaIndex).
Experience designing AI evaluation systems beyond basic metrics and managing structured output enforcement in production systems.
Work Experience Required: 10+ years in relevant AI/NLP domain with leadership experience; other hard qualifications per above; Notice period: Not explicitly mentioned in the JD.
Experienced in building complex AI workflows and architectures specifically for financial document processing, preferably with domain knowledge in KYC/AML.
Able to lead sizable technical teams in fast-evolving AI environments requiring pragmatic trade-offs and cross-stakeholder communication, including with compliance and risk teams.
Skilled in integrating advanced AI concepts including autonomous agents, security, multi-modal AI, and AI observability for regulated financial settings.