Generative AI Architect

AIML GenAI Architect

Key Responsibilities

GenAI Agentic AI Strategy

Select and optimize opensource LLMs Llama 3 Mistral Falcon BLOOM for local deployment lead finetuning using PEFTLoRAQLoRA and full finetuning strategies

Architect LLM distillation pipelines to create smaller domainspecific models for inference efficiency

Design and govern RAG pipelines standard RAG Graph RAG Hybrid RAG for chatbots grievance redressal helpdesk automation and document summarization

Build reusable AI Agent frameworks task agents reasoning agents retrieval agents workflow managers using LangGraph and AutoGen

Architect multiagent orchestration systems with supervisorworker patterns tooluse agents and selfreflection loops

Classical ML Advanced Analytics

Design ML pipelines for calibration models ensemble models stacking blending boosting upliftcausal ML models and simulation models

Establish XAI Explainable AI frameworks using SHAP LIME Integrated Gradients define interpretability standards for regulatory compliance

LLM Evaluation Quality Frameworks

Create accuracy and evaluation frameworks for summarization ROUGE BERTScore LLMasjudge extraction classification and conversational AI

Implement hallucination detection factuality scoring and bias evaluation frameworks using LangKit GuardrailsAI and custom evaluators

Define LLM evaluation benchmarks aligned to use cases establish continuous evaluation pipelines triggered post finetuning

Govern prompt engineering standards fewshot template libraries and chainofthought reasoning frameworks

Document Intelligence Knowledge Pipelines

Build document intelligence workflows OCR Tesseract PaddleOCR parsing chunking strategies embeddings summarization extraction QA