Gautam Gaur

Directed and scaled a 15-18 member cross-functional organization across AI, Data Science, UI/UX, and Engineering, driving technical vision, execution strategy, and enterprise delivery across multiple high-impact initiatives. Conceived, architected, and led the rollout of PN-Os (Perceive Now Operating System), a foundational enterprise AI platform powering multi-agent orchestration, autonomous reasoning, intelligent workflows, and large-scale report generation systems. Designed and operationalized enterprise-grade AI infrastructure and workflow systems that contributed to $5M+ in enterprise opportunities, strategic partnerships, and high-value client engagements. Partnered directly with founders, executive stakeholders, and enterprise customers to shape product strategy, define technical roadmaps, and translate business requirements into scalable AI products. Established technical standards, architecture principles, and delivery governance frameworks to ensure scalability, reliability, and production excellence across AI platforms. Drove creation of defensible AI IP, strengthening product differentiation, accelerating customer acquisition, and supporting long-term commercial growth. Led strategic decisions across AI architecture, deployment strategy, and system design while balancing research innovation, engineering execution, and business objectives.

Architected Multi-Agent Orchestration Systems (MCP/Swarm) achieving the highest levels of accuracy and reliability across large-scale AI pipelines. Built LLM-powered Conversational Systems featuring Live Data Extraction, AdTech-grade personalization, audience segmentation, and dynamic recommendation logic, incorporating contextual fidelity and hallucination mitigation layers. Designed End-to-End RAG Pipelines (LangGraph/LangChain) utilizing Pinecone, Weaviate, and Redis for advanced campaign intelligence, creative optimization, and A/B testing automation. Developed Graph-based PDF Reporting, AI-powered data visualization dashboards, and evidence-linked insights for marketing performance and budget optimization. Created Proprietary IP by establishing defensible algorithms and validation pipelines, directly supporting funding rounds and production-level deployments. Integrated OCR/VLM Models (Docling, GPT-OSS, MonkeyOCR, Tesseract) for Multimodal Insights and implemented Blockchain-secure Logging & Compliance Layers for sensitive data environments. Collaborated with Big Tech partners to enhance interoperability, model compliance, and data governance across enterprise integrations. Led a 5 member Data Science Team in IP defensibility, benchmarking, contradiction detection, and statistical quality assurance, powering major funding rounds and production deployments.

Led R&D on advanced AI systems, architecting and deploying SOTA tech from scratch to production. Developed AI text detection (95%+ accuracy), CNN-based AI image detector, and a stylometric AI humanizer model that outperformed commercial detectors with lower false positives and higher fidelity. Engineered high-throughput pipelines for synthetic data generation & multimodal detection, leveraging Transformers, Contrastive Learning, Forensic Features, ANN/GNN, and RL/DL/ML orchestration. Built and applied Model Quantization for faster inference, reduced costs, and compliance-ready resilience. Scaled platform to 20M+ users, ranked #2 globally on benchmarking (precision-recall metrics), and drove 5x revenue growth through enterprise-scale capabilities and tools like an AI-powered job filler automation system.

Designed & developed REST APIs with FastAPI, enabling seamless data exchange and stronger system integration. Automated community engagement on Facebook, Instagram, LinkedIn, and Twitter using social media APIs + Python scripting, boosting brand visibility. Integrated OpenAI API for full-scale automation, enabling autonomous customer responses and improving satisfaction & response times. Built AI-driven content automation (image/video generation & posting) and connected Salesforce plus Smartsheet APIs, streamlining data collection & workflows. Developed Google Calendar, Google Docs, Dropbox, and WhatsApp APIs, optimizing data management, communication, and client services in Generative AI systems.

Built LinkedIn scrapers with Python & Selenium and automated PDF data extraction using Tesseract OCR and OpenCV. Applied prompt engineering with ChatGPT API and performed application analysis & design for intelligent automation. Developed lead-generation automation tools (contact form filler), cutting costs and boosting efficiency; implemented Python unit testing for reliability.

Builted OpenAI-powered chatbots and designed automation pipelines, improving efficiency and reducing manual effort. Developed scalable microservices (FastAPI) and implemented RBAC-secured databases for reliable, secure data handling. Engineered a Smart Entry System using RFID and QR technologies, enhancing access control and user convenience. Contributed to Automobile Supply Chain Management solutions, driving efficiency and data integration.