Description
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.

Responsibilities
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.

Qualifications
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.

📌 AVP, GenAI Enterprise Architect (Gurugram)
🏢 EXL
📍 Gurugram