AVP, GenAI Enterprise Architect

Role Overview

Design and deploy enterprise-grade AI solutions (LLMs, RAG, agents) by

selecting appropriate models, building data pipelines, and integrating them with cloud platforms

(AWS, Azure, GCP). Lead technical strategies, ensure scalability, manage AI security/

hallucinations, and bridge business needs with engineering teams.

Key Responsibilities

System Design & Architecture

Architect end-to-end Generative AI systems, including

retrieval-augmented generation (RAG) and vector data systems.

Model Selection & Tuning

Evaluate and select cutting-edge commercial (e.g., GPT-4) and

open-source models, and fine-tune models for domain-specific use cases.

LLMOps & Pipelines

Establish LLMOps standards for model versioning, evaluation, prompt

management, and CI/CD, ensuring robust, production-grade AI.

Integration & Security

Integrate AI solutions with existing APIs, applications, and databases

while enforcing security, privacy, and guardrails to manage hallucinations and adversarial

attacks.

Strategic Leadership

Collaborate with stakeholders to map business challenges to AI

solutions and establish AI governance frameworks.

Bachelor’s / Master’s in Computer Science, AI, Data Science, or related field;

8–15 years in software engineering, ML, or AI roles. Experience with enterprise-level systems.