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Tier-1 bank brand attracts candidates, but senior, niche agentic AI requirements reduce applicant density.
Strong AI engineering focus plus banking regulatory and enterprise deployment needs make cross-industry transitions harder.
Explicit 10+ years, mandated AI experience, and extensive tech stack and banking constraints increase filtering.
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Lead full-stack design, implementation, and deployment of scalable agentic AI frameworks and generative AI solutions tailored for banking use cases.
Drive rapid development cycles focusing on MVPs, hypothesis testing, and continuous improvement via metrics and A/B experimentation.
Provide hands-on technical leadership and collaborate with AI researchers, data scientists, product managers, and engineers to integrate AI solutions across Citi's products.
10+ years of progressive software engineering experience with strong hands-on coding and rapid delivery of AI features.
Minimum 3+ years of professional experience focused on AI, prompt engineering, machine learning, generative and/or agentic AI systems.
Bachelor’s degree in Computer Science, Information Technology, Artificial Intelligence, Robotics, or related quantitative field (Master's preferred).
Expert proficiency in Python frameworks (FastAPI, Django, Flask, PySpark) and experience with ML frameworks like TensorFlow, PyTorch; hands-on with Docker and Kubernetes; experience in banking or financial services preferred.
Experienced in architecting and delivering enterprise-scale AI projects, including agent-based and autonomous AI systems within a regulated banking environment.
Technical leader capable of hands-on contribution and guiding cross-functional teams in a fast-paced, iterative development setting.
Strong background in system design, API-first microservices architecture, and integrating large language models (LLMs) into operational AI systems.