Assistant Vice President - Data Science

Навыки

• AI-агенты
• AI-инструменты в работе
• Распределённые системы
• Kubernetes
• Лидерство
• Machine Learning
• MLOps

О компании и продукте

• Job Overview The Lead AI Engineer is a senior individual contributor and the primary technical owner for complex AI projects. This role focuses on the hands-on architecture and implementation of cutting-edge AI solutions, ensuring technical excellence and alignment with product goals.

Задачи

• rimary Responsibilities (60%)
• Serve as the technical anchor for the development of enterprise-grade, AI-powered solutions, guiding the implementation from a technical perspective
• Lead the hands-on implementation of novel AI solutions, particularly in autonomous agents and advanced agentic architectures (e.g., using Google ADK)
• Architect and implement advanced frameworks for AgentOps and agentic AI governance, including evaluation suites, post-production observability, and traceability mechanisms
• Secondary Responsibilities (30%)
• Partner with product leadership to shape the AI product strategy and technical roadmap
• Technically lead the reimagination of core business processes by designing and implementing novel AI-driven solutions
• Collaborate cross-functionally with Technology, Model Risk Management (MRM), Legal, Compliance, and Business teams to ensure solutions are robust, compliant, and aligned with enterprise goals
• Additional Responsibilities (10%)
• Evangelize AI best practices across the organization
• Lead the evaluation and integration of emerging AI technologies
• Leadership & Collaboration / Dual-Track Path
• Technical Leadership (Individual Contributor Track): Focus on solving the most challenging technical problems, pioneering new AI capabilities, and acting as a subject matter expert
• People Leadership (Manager Track): Guide and grow a team of AI engineers, balancing hands-on technical contribution with coaching, performance management, and strategic project oversight

Требования

• Experience: 8–10 years of professional experience in software engineering, with a significant focus on building and deploying large-scale AI/ML systems
• Knowledge and Skills (Required): Expertise in Python
• Proven experience architecting and building complex systems using agentic frameworks (e.g., Google ADK, LangChain, AutoGen)
• Deep expertise in context optimization, knowledge storage (vector databases, knowledge graphs), and Retrieval-Augmented Generation (RAG) at scale
• Strong architectural skills in designing complex, distributed systems and scalable backend APIs
• Expertise in defining and implementing evaluation strategies using platforms like LangFuse
• Knowledge and Skills (Preferred): Experience building control and sandboxing systems for AI research
• Contributions to open-source AI or cloud-native projects
• Experience in the financial services industry
• Deep hands-on knowledge of Kubernetes
• Extensive experience with deep learning frameworks and MLOps principles
• Certifications: Advanced certifications in Gen AI , Agentic AI, cloud architecture, Kubernetes, or machine learning are a strong plus
• Education Bachelor's/University degree in Computer Science or a related field
• Master's degree is highly preferred
• Job Family Group: Decision Management
• Job Family: Specialized Analytics (Data Science/Computational Statistics)
• Time Type: Full time
• Most Relevant Skills Please see the requirements listed above
• Other Relevant Skills For complementary skills, please see above and/or contact the recruiter
• Citi is an equal opportunity employer, and qualified candidates will receive consideration without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other characteristic protected by law
• If you are a person with a disability and need a reasonable accommodation to use our search tools and/or apply for a career opportunity review Accessibility at Citi
• View Citi’s EEO Policy Statement and the Know Your Rights poster

Паспорт вакансии

История публикации

Откуда что взялось

Отмечено то, что вывели мы. Без пометки — значение назвал работодатель.

Почему на этом месте в выдаче

Порядок выдачи объявлен контрактом: свежесть решает между днями, полнота и зарплата — внутри дня.