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Protocol Intelligence
Data-driven signals on your job's competitivenessTier-1 employer, mid-level GenAI role in metro with broad talent demand and strong brand.
Core GenAI skills are transferable across industries, though banking experience is preferred.
Explicit 5–8 years plus mandatory LLM, GenAI, and MLOps skills enforce strict screening.
Job Description
Structured overview of role & requirementsAbout This Role
Lead end-to-end development and deployment of AI-powered products focusing on client experience and operations in Treasury & Trade Services.
Analyze complex business data including unstructured sources (emails, call transcripts) to generate actionable insights and solutions using Gen AI and deep learning techniques.
Collaborate cross-functionally to ideate and deliver AI solutions addressing strategic business priorities while ensuring compliance and risk management.
Minimum Requirements
5 to 8 years of experience in Data Science including Machine Learning and Deep Learning; at least 2 years experience with Generative AI solutions.
Strong experience shipping AI-enabled products to production in Agile environments and working with LLMs, transformer models, and GenAI techniques like prompt engineering and RAG.
Proficiency with frameworks such as PyTorch, TensorFlow, and Hugging Face, and skills in MLOps for GenAI including deployment, monitoring, and optimization.
Preferred Masters degree in Computer Science Engineering; work experience in financial services or related domains is highly relevant but not strictly stated as mandatory.
Ideal Candidate Profile
Experienced in solving client experience and operations problems within financial services or similarly complex data environments using advanced AI and analytical tools.
Comfortable managing ambiguous, open-ended problems and driving AI product delivery end-to-end including design, testing, deployment, and operational support.
Skilled at collaborating with cross-functional teams across product, business, data, and operations to translate strategic priorities into AI-driven business outcomes.