Assistant Vice President - Data Science

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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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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