Senior Python Data and AI Engineer - Vice President

Working at Citi is far more than just a job. A career with us means joining a team of approximately 219,000 dedicated people from around the globe. At Citi, you’ll have the opportunity to grow your career, give back to your community and make a real impact.

Experience: At least 10+ years of hands-on application development experience. Design, develop, and maintain ETL processes to extract, transform, and load data from various sources into our data warehouse. Write complex SQL queries and PL/SQL scripts to perform data manipulation, validation, and transformation. Develop and maintain data pipelines using Python and related libraries (e.g., Polar ,Pandas). Optimize ETL processes and data pipelines for performance and scalability. Collaborate with data analysts and other stakeholders to understand data requirements and develop solutions to meet their needs. Implement data quality checks and monitoring to ensure data accuracy and consistency. Troubleshoot and resolve data-related issues. Create and maintain technical documentation for ETL processes, data pipelines, and database solutions. Stay up-to-date with the latest trends and technologies in data management and analytics.

Database Knowledge: Strong knowledge of databases such as Oracle/MY SQL/SQL. Scripting: Strong knowledge of Python . Problem-Solving: Excellent analytical and problem-solving skills. Communication: Strong communication and interpersonal skills. Teamwork: Ability to work effectively in a team environment. Methodology of AI includes Chunking, Embedding, AI Engineering, Prompt Engineering

Deep hands-on experience in engineering and executing scalable enterprise solutions. Expert-level proficiency in Python (e.g., FastAPI, Flask, PySpark) Proficiency in database technologies, such as Oracle, Postgres, or MongoDB. Solid understanding of core AI concepts, including knowledge representation, automated planning, decision-making under uncertainty, and multi-agent systems. Hands-on experience with relevant frameworks (e.g., Google ADK, LanGraph, LangChain, AutoGen, CrewAI, N8N). Good to have experience with machine learning frameworks (e.g., TensorFlow, PyTorch) and relevant libraries (e.g., Scikit-Learn, NumPy, Pandas). Proven experience in creating, deploying, and integrating MCPs (Model Context Protocol) into agentic AI systems. Deep familiarity with large language models (LLMs) such as ChatGPT, Claude, Gemini, and Llama, including their application within agentic systems. Demonstrated experience in designing and implementing robust APIs for AI services. Proficient in software development best practices, including version control (Git), CI/CD pipelines, comprehensive testing, and code reviews. Strong understanding of agile methodologies, application resiliency, and security principles applied to complex AI projects. Proven expertise in system design, application development, and ensuring operational stability for AI initiatives. Deep experience with application and data architecture patterns and designs. Experience leveraging managed services and existing platforms, with a strong emphasis on API-First Design, microservices, and event-driven architectures. Hands-on experience with Docker and Openshift.

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