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, p...