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.

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• 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

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