Assistant Vice President - Data Science

C12: Lead AI Engineer Job Title: Lead AI Engineer Job Code: TBD Job Family Group: Decision Management Job Family: Specialized Analytics (Data Science/Computational Statistics) Citi Job Level: C12 Exemption Status: EXEMPT Manager Level: INDIV. CONTRIB 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. Responsibilities Primary 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. Qualifications 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. 609912

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.

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