Gen AI Tech Lead Engineer - Vice President

Gen AI Tech Lead Engineer - Vice President
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Overview of Citi:  Citi is a world‑leading global bank. It has approximately 200 million customer accounts and a presence in more than 100 countries. Citi provides consumers, corporations, governments, and institutions with a broad range of financial products and services, including consumer banking, corporate and investment banking, securities brokerage, transaction services, and wealth management. Citi’s mission is to enable clients to achieve their strategic financial objectives by delivering cutting‑edge ideas, best‑in‑class products, and unparalleled access to capital and liquidity.

Overview of the organization:  The COO Enterprise Solution Engineering capability is responsible for developing best‑in‑class technology platforms for Operations. Key responsibilities include creating an integrated portfolio of Operations tools, designing end‑to‑end solutions for large‑scale transformation initiatives, establishing design governance, and adopting Generative AI solutions to drive operational efficiencies.

Role:  This position is for an innovative Generative AI Engineer focused on adopting Large Language Models (LLMs) and agentic flows. The successful candidate will advance the technical direction of products and services, instill engineering best practices, and promote cultural change within the organization. Responsibilities include collaborating with technology teams to expand Generative AI across enterprise‑wide applications, and building partnerships with third‑party providers to validate and adopt best‑of‑breed solutions.

Responsibilities

Contribute significantly to engineering and research initiatives within the Generative AI domain.

Adopt a product‑focused approach, ensuring the development of robust, scalable, and user‑friendly solutions.

Thrive in a fast‑paced environment by continuously testing, learning, and tackling cutting‑edge problems.

Actively engage in pair programming, promote lean methodologies, and streamline processes by removing unnecessary bureaucracy.

Prioritize rapid delivery and iterative development, demonstrating adaptability and a willingness to pivot rather than pursuing a perfect upfront solution.

Develop foundational components and mature technology capabilities in Artificial Intelligence (AI) and LLMs.

Drive enterprise‑wide adoption and successful integration of Generative AI solutions.

Demonstrate strong problem‑solving capabilities and a proactive learning mindset, continuously acquiring new skills.

Exhibit excellent communication and collaboration skills, effectively engaging with diverse stakeholders.

Be adaptable and resourceful in navigating complex technical and organizational challenges.

Appropriately assess risk when business decisions are made, demonstrating sound ethical judgment and particular consideration for the firm’s reputation, clients, and assets.

Required Skills, Knowledge & Experience
Technical Expertise

Deep hands‑on experience engineering and executing enterprise solutions that scale effectively.

Fluency in at least two programming languages, with a strong preference for Python and Java. Proficiency in JavaScript/Type Script and Golang is also highly valued.

Strong understanding of Language Models (LLMs), transformers, agentic frameworks, vector stores, and search algorithms.

Experience with frameworks such as Spring (AI, Boot, Core, etc.), N8N, Flask, Lang Chain, Lang Graph, and MLFlow.

Proficiency in database technologies such as Oracle, Postgre

SQL, or Mongo

DB.

Experience with messaging and integration platforms like Kafka or JMS/MQ.

UI development skills using React.js or Streamlit.

Experience designing and implementing REST and Web Socket APIs.

Familiarity with one of the major cloud platforms: AWS, GCP, or Azure.

Strong knowledge of infrastructure tools:
Docker, Kubernetes, Terraform, and Helm.

Experience with build and deployment (CI/CD) tools such as Jenkins and Gradle.

Good engineering experience with high‑performance, large‑scale AI/ML systems.

Experience in model risk management, guardrails development, and creating end‑user adoption pathways for AI/GenAI solutions.

Genera…