Role Summary: The AI/ML Engineering Head leads the development of the intelligence layer for vertical offerings. The position is responsible for ensuring models are accurate, context-aware, and compliant with enterprise-grade safety and governance standards. This person may also be required to lead model finetuning activities to meet customer requirements, if necessary.

Job Responsibilities:

• RAG Pipeline Development: Design and optimize Retrieval-Augmented Generation (RAG) systems to process unstructured enterprise data into actionable intelligence.
• Model Governance: Implement safety guardrails and robust monitoring to prevent hallucinations and ensure brand-aligned responses.
• Inference Optimization: Oversee the optimization of models to run efficiently across diverse hardware architectures and distributed cloud/edge environments.
• Knowledge Readiness: Manage data/knowledge readiness cycles to ensure the AI remains updated with client-specific information.
• Domain-Specific Model Fine-Tuning: Adapt the model by leveraging client data and expertise to address specific customer requirements.

Job Requirements:

• AI Foundations: Master’s or PhD in AI, ML, or Computer Science with 6+ years in applied ML roles.
• NLP Specialization: Extensive experience with Large Language Models (LLMs), vector databases, and semantic search.
• Performance Tuning: Expertise in model quantization and performance tuning for resource-constrained edge hardware.
• Governance Knowledge: Understanding of AI ethics, data privacy regulations, and secure prompting techniques.