About Naveen
English
Fluent
Experience
- ADEK & WatermelonLead AI Architect / AI Product ManagerApril 2025 - Today (1 year and 2 months)United Arab Emirates• • Architected and deployed enterprise GenAI platforms (LLM agents, agentic workflows, RAG chatbots) using Claude Code, Google Antigravity and Gemini (Vertex AI), serving 10K+ daily requests, improving user engagement by 40% and reducing operational costs by ~30%.• • Designed end-to-end production AI systems (data ingestion → retrieval → inference → evaluation → monitoring) with distributed microservices architecture, reducing latency by 40% and improving system reliability to 98% uptime.• • Led LLM fine-tuning (LoRA/QLoRA), prompt engineering, and hallucination mitigation, improving response accuracy by 30–40% and reducing hallucinations by ~30%.• • Built and deployed AI agents and Automation workflows using n8n and LLM APIs, integrating with business tools (CRM, Google Workspace, APIs) to automate real-world operational processes.• • Designed and deployed agentic systems with multi-step reasoning, tool usage, and workflow orchestration using LangGraph and custom Python pipeline.• • Delivered A/B tested AI solutions driving 20% reduction in churn and increased product engagement across UAE & GCC markets, built scalable MLOps pipelines (CI/CD, MLflow, Docker, FastAPI, Kubernetes), reducing deployment time from weeks to days and enabling continuous delivery of production AI systems.• • Partnered with stakeholders to define AI strategy, KPIs, and ROI-driven use cases, aligning AI initiatives with business outcomes• • Evaluated and deployed self-hosted LLMs (via Ollama/vLLM) vs cloud models based on latency, cost and data privacy requirements.• • Rapidly prototyped and shipped AI tools (v1 within days), iterating based on real user feedback and operational needs.
- Circle K & Huloop.aiLead Data ScientistJuly 2022 - April 2025 (2 years and 9 months)• • Built and deployed advanced Agentic RAG systems (Hybrid retrieval, re-ranking, tool orchestration), improving answer relevance by 25% and reducing support resolution time by 40% using OpenAI, Claude, Llama, LangChain, and vector DBs (FAISS, Pinecone), developed scalable LLM APIs (FastAPI + MLflow) supporting real-time inference at production scale.• • Built large-scale data integration pipelines (batch + real-time via Kafka/Airflow) consolidating multiple data sources, improving data availability and reducing processing latency by ~30%• • Defined data and AI architecture roadmaps aligned with business goals, collaborating with cross-functional teams (AI/ML, product, business) to drive data-driven decision-making and platform scalability.• • Implemented LLM fine-tuning (PEFT, LoRA, QLoRA) improving model performance and reducing inference cost• • Delivered $600K/year cost savings, led cross-functional teams for AI product delivery, architecture decisions and deployment strategies.
- PIMCO, BMS & NFLSenior Data Scientist/ ML EngineerJanuary 2020 - July 2022 (2 years and 6 months)• • Developed ML and AI solutions including recommendation systems, RL models, fraud detection, and forecasting systems.• • Built production ML pipelines using Python, SQL, and MLOps frameworks.
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Education
- B. EngineeringPanjab UniversityB. Engineering