I am a data analyst turned AI architect with 5+ years of experience building production systems across analytics, ML, and autonomous AI. I designed and deployed Aubos.ai — a full Autonomous Business Operating System running 400+ active AI agents, delivering 100x faster execution and 90% cost reduction versus traditional teams. I currently operate the platform in production, where it has eliminated $450K+ in annual overhead with zero ops headcount. My core expertise includes agentic AI orchestration, RAG pipeline engineering, multi-model routing, LLM fine-tuning, and generative media automation.

Vaibhav Salonia

I am a data analyst turned AI architect with 5+ years of experience building production systems across analytics, ML, and autonomous AI. I designed and deployed Aubos.ai — a full Autonomous Business Operating System running 400+ active AI agents, delivering 100x faster execution and 90% cost reduction versus traditional teams. I currently operate the platform in production, where it has eliminated $450K+ in annual overhead with zero ops headcount. My core expertise includes agentic AI orchestration, RAG pipeline engineering, multi-model routing, LLM fine-tuning, and generative media automation.

Available to hire

I am a data analyst turned AI architect with 5+ years of experience building production systems across analytics, ML, and autonomous AI. I designed and deployed Aubos.ai — a full Autonomous Business Operating System running 400+ active AI agents, delivering 100x faster execution and 90% cost reduction versus traditional teams.
I currently operate the platform in production, where it has eliminated $450K+ in annual overhead with zero ops headcount. My core expertise includes agentic AI orchestration, RAG pipeline engineering, multi-model routing, LLM fine-tuning, and generative media automation.

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Language

English
Fluent

Work Experience

Chief Technology Officer (CTO) at EM Devices dba DrinGIO Tech
June 1, 2025 - Present
Architected a 400+ agent fully autonomous AI ecosystem that eliminated traditional ops team overhead, reducing annual OpEx by $450K+ (85%), while accelerating output velocity by 10x across all business functions. Built a centralized Model Context Pro to maintain state across distributed agents for complex, multi-turn decision making; engineered high-throughput RAG pipelines with vector data stores to ground LLMs in company data and reduce hallucinations. Developed a proprietary Model Router that dynamically dispatches tasks to optimal models across DeepSeek, Grok, Gemini, Claude, and OpenAI for instruction following while controlling costs. Created a Generative Content Engine: automated video production pipelines and a fine-tuned image system producing 200+ brand-consistent content pieces per month with zero human touch points. Deployed self-optimizing systems with autonomous marketing agents that self-heal and adjust creative direction. Achieved sub-100ms AI agent response times via R
Data Analytics & ML Intern at HP Inc.
July 1, 2024 - September 30, 2024
Audited 150+ SKUs for cost and margin optimization; delivered data-backed insights that reshaped product road map and pricing strategy, identifying $1M+ in addressable revenue opportunity. Deployed Gradient Boosting models for competitive market analysis across 8 global regions, achieving 95% insight accuracy to support targeted go-to-market decisions.
Senior Data Analyst at Pacific Global, Inc.
October 1, 2022 - August 31, 2023
Pipeline Automation: Automated 80% of ETL processes via Apache Airflow and implemented Spark Streaming for 300K+ events/sec, significantly increasing data availability and reducing manual error rates. Performance Engineering: Engineered multi-layered Spark architectures (AQE, Broadcast joins) that reduced memory usage by 20% and boosted query performance by 60% at scale.
Executive Data Analyst at EPROSIGN Technical Solution Pvt Ltd
April 1, 2019 - September 30, 2022
Automation at Scale: Automated 95% of recurring ETL jobs using Python and Airflow, saving 80+ hours/month and reducing reporting time by 50% and pipeline failures by 70%. Infrastructure Optimization: Slashed SQL query costs by 40% and improved dashboard responsiveness through denormalized views, materialized views, and time-series forecasting models.

Education

Master of Professional Studies (MPS) in Analytics at Northeastern University
January 11, 2030 - December 1, 2024
Bachelor of Technology in Computer Science Engineering at Guru Gobind Singh Indraprastha University
January 11, 2030 - August 1, 2019

Qualifications

Add your qualifications or awards here.

Industry Experience

Software & Internet, Media & Entertainment, Professional Services, Computers & Electronics