Assistant Vice President - Data Science

Citi; Bengaluru; On-site; INR 2,678,400 - 4,017,600; Full time

Job summary

Citi is seeking a Lead AI Engineer to be the primary technical owner for complex AI projects in Bengaluru, India. This senior role focuses on hands-on architecture and the implementation of cutting-edge AI solutions aimed at achieving technical excellence.

The ideal candidate will have 8–10 years of experience in software engineering with proven expertise in architecting AI systems. Responsibilities include collaborating with product teams and leading the development of AI solutions that align with business goals.

Qualifications

• 8–10 years of professional experience in software engineering.
• Significant focus on building and deploying large-scale AI/ML systems.
• Experience in the financial services industry preferred.

Responsibilities

• Serve as the technical anchor for enterprise-grade AI solutions.
• Lead hands-on implementation of novel AI solutions.
• Collaborate cross-functionally to ensure compliance and robustness.

Skills

Python

Architecting complex systems

Context optimization

Knowledge storage (vector databases, knowledge graphs)

Designing complex distributed systems

Kubernetes

Education

Bachelor's/University degree in Computer Science

Master's degree

Tools

Google ADK

LangChain

AutoGen

Job description

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.

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.

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