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Tier-1 brand, metro location, and sought-after ML/AI domain increase applicant competition moderately.
Strong ML/AI specialization transfers across industries, though banking/regulatory experience is preferred.
Explicit 10+ years and many mandatory ML/AI, infra, and banking-related technical skills imply stringent filters.
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Lead design, development, and deployment of scalable, robust agentic AI frameworks and generative AI solutions for critical banking use cases.
Build full-stack applications integrating ML/LLM tools to deliver AI solutions with rapid iteration and continuous optimization.
Provide hands-on technical leadership and collaborate with cross-functional teams to scale AI solutions across Citi's products.
10+ years progressive software engineering experience with hands-on coding and rapid delivery of AI features into production.
Minimum 3+ years professional experience in AI, prompt engineering, machine learning, generative or agentic AI systems.
Bachelor’s degree in Computer Science, IT, AI, Robotics or related quantitative field; Master’s preferred.
Proficiency in Python (FastAPI, Django, Flask, PySpark), ML frameworks (TensorFlow, PyTorch), and AI system design including APIs and agentic systems.
Experienced technical leader with deep hands-on expertise in architecting enterprise-scale AI projects in banking or financial services contexts.
Competent in full-stack AI solution development integrating LLMs, multi-agent systems, and modern software engineering (CI/CD, containerization).
Proven ability to lead complex AI architecture decisions and collaborate with AI researchers, data scientists, and product managers in regulated environments.