Rajnish

Rajnish

$80/hr
Enterprise GenAI, Agentic AI, RAG, Multi-Agent Systems & MLOps
Reply rate:
-
Availability:
Hourly ($/hour)
Age:
34 years old
Location:
Delhi, Delhi, India
Experience:
13 years
About

Overview I am a Visionary AI Architect and Executive with a proven track record of driving business scaling and generating $5M+ in revenue through high-impact GenAI implementations. I specialize in bridging the gap between advanced research—such as Multi-Agent Orchestration and Transformers—and production-grade software engineering. I have successfully established AI Centers of Excellence and scaled cross-functional teams from 3 to 21+ members.

Professional Work Experience

**Chief Artificial Intelligence Officer (CAIO) | AcadAlly (Nov 2024 – Present) **

Agentic AI Architecture: Architected a Multi-Agent System using LangGraph (Planner, Tutor, Critic agents) for an Intelligent Tutoring platform.

Deep Learning: Designed the "Student Clone" predictor, a model forecasting academic performance with 92% accuracy.

Text-to-SQL Automation: Deployed "Text2Mongo," cutting analytics turnaround time by 80%.

**Senior Generative AI Advisor | Cigna Healthcare (Evernorth) (Dec 2023 – Oct 2024) **

Healthcare GenAI: Designed the "Evident App," a secure NL2SQL platform for querying patient databases with strict HIPAA compliance.

Computer Vision: Developed a Claim Audit Platform using GPT-4 Vision, reducing manual audit effort by 40% with 95%+ accuracy.

**Principal Data Scientist | Times Internet (Jan 2022 – Dec 2023) **

Ad-Tech Integration: Pioneered the Ad-GPT Platform to generate context-aware ad creatives.

Revenue Impact: Optimized CTR prediction models delivered a $3M+ revenue uplift.

**AI Architect (Group Manager) | Evalueserve(Jan 2013 – Dec 2021) **

Product Architecture: Built the AIRA cognitive AI solution, generating $2.7M in revenue.

Financial Automation: Designed SpreadSmart, generating $0.8M annually through operational efficiency.

Technical Capabilities

LLMs & GenAI: GPT-4o, Claude 3.5 Sonnet, Llama 3, Fine-tuning (PEFT/LORA).

Agentic AI: Multi-Agent Systems (MAS), LangGraph, CrewAI, AutoGen.

RAG & Vector: Hybrid Search, GraphRAG, Pinecone, Weaviate.

I am looking for challenging enterprise projects where I can leverage Agentic AI and Deep Learning to solve complex bottlenecks.

Languages
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