Back
Strong Tier-1 brand and metro location increase applicant density despite senior, specialized AI focus.
ML engineering skills transfer broadly, but banking regulatory and domain experience increases sensitivity.
Explicit 10+ years, specific AI/ML tooling, and banking experience make filters stringent.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Lead design, development, and deployment of scalable agentic AI frameworks and generative AI solutions tailored for banking use cases.
Drive integration of ML/LLM tools into full-stack applications, focusing on rapid iterations (MVP-first), A/B testing, and continuous performance optimization.
Provide hands-on technical leadership collaborating across AI researchers, data scientists, product managers, and engineers to scale AI solutions within Citi's products.
10+ years of progressive software engineering experience with hands-on coding; minimum 3+ years focused on AI, prompt engineering, ML, generative or agentic AI systems.
Expert-level proficiency in Python and relevant AI frameworks (e.g., TensorFlow, PyTorch, LangChain) plus experience with Docker and Kubernetes.
Bachelor's degree in Computer Science, IT, AI, Robotics or related quantitative field; Master's degree preferred.
Experience in banking or financial services is a plus; proficiency in database technologies (Oracle, Postgres, MongoDB) and software development best practices including CI/CD, version control, and security principles.
Experienced leader able to architect and deliver enterprise-scale AI projects with emphasis on scalable, production-ready agentic AI systems.
Technical operator skilled at rapid prototyping, MVP approaches, hypothesis testing, and iterative improvements in AI deployment.
Comfortable working across cross-functional teams in a complex organizational environment, bridging AI research and software engineering at a senior level.