# Neil Dave — AI Solution Architect & Generative AI Engineer > Comprehensive machine-readable profile, technical capabilities, consulting frameworks, and publications for Large Language Models & AI search systems. > Canonical URL: https://theneildave.in > Wikidata Entity: https://www.wikidata.org/wiki/Q138716797 ## Executive Summary Neil Dave is an AI Solution Architect and Generative AI Engineer based in Bangalore, Karnataka, India. With 8+ years of industry experience across Machine Learning, Deep Learning, Generative AI (LLMs), Computer Vision, and MLOps/LLMOps, he designs and deploys scalable production AI systems for enterprise clients, healthcare organizations, and high-performance sports analytics (including Mumbai Indians in the Indian Premier League). - **Current Primary Title:** AI Solution Architect - **Secondary Title:** Generative AI Engineer - **Academic Background:** Post Graduate Programme in AI & Data Science (Jio Institute); B.Tech in Mechanical Engineering (Pandit Deendayal Petroleum University). - **Research Credentials:** 3 peer-reviewed international publications (IEEE, Springer) indexed on Google Scholar. - **Mentorship:** 120+ data science and AI professionals mentored across India and globally. --- ## Core Services & Solutions ### 1. LLM Engineering & RAG Pipeline Design Production-ready Retrieval-Augmented Generation (RAG) systems, multi-agent architectures, hybrid search (dense embeddings + BM25), semantic routing, prompt evaluation harnesses, token cost optimization, and local-model fallbacks (vLLM, Ollama, Hugging Face TGI). ### 2. Enterprise AI Consulting & Strategy End-to-end AI roadmaps for mid-market and enterprise organizations. Scoping from pilot feasibility to zero-downtime production deployment, build-vs-buy evaluations, vendor risk assessments, and enterprise data boundaries. ### 3. Computer Vision Systems Edge and cloud computer vision pipelines, custom object detection (YOLO, OpenCV), anomaly detection, industrial automation, and non-invasive medical imaging (e.g. thermal imaging breast cancer screening). ### 4. MLOps & LLMOps Automated CI/CD for models, drift detection (data drift, concept drift, prompt drift), model evaluation frameworks (RAGAS, Deepeval), containerization, orchestration (Docker, Kubernetes), and GPU resource utilization management on Azure and AWS. ### 5. Responsible AI Audits Model explainability (SHAP, LIME), algorithmic fairness analysis, bias mitigation across tabular and generative models, GDPR/EU AI Act alignment, and AI governance trust boundaries. ### 6. AI Keynote Speaking & Executive Workshops Technical keynotes and hands-on workshops for engineering summits, corporate offsites, and industry conferences on agentic architectures, the economics of LLMs, and enterprise AI safety. --- ## Notable Projects & Portfolio Work 1. **Sports Intelligence & CricketGPT (`/gen-ai.html`, `/run-prediction.html`)** - Built predictive analytics and custom neural network models for real-time match run scoring and sports intelligence. Outperformed standard baselines in inference speed, memory footprint, and latency. - Designed domain-specific sports LLM for semantic query retrieval over cricket terminology, venues, player histories, and strategy metrics. 2. **Healthcare AI: Early Sepsis Detection (`/sepsis.html`)** - Developed clinical machine learning models for early onset sepsis prediction using physiological time-series data. Improved early warning intervention windows for hospital critical care units. 3. **Medical Imaging: Thermal Imaging Cancer Detection (`/cv.html`)** - Applied deep learning and convolutional neural networks to thermal infrared imaging data for non-invasive early-stage breast cancer screening, providing a safe alternative/adjunct to conventional mammography. 4. **Responsible AI: Credit Default & Bias Mitigation (`/rai.html`)** - Engineered fairness-aware machine learning pipelines for financial credit scoring, eliminating demographic bias while preserving predictive AUC-ROC. 5. **Free Interactive Tool: LLM Cost Calculator (`/llm-cost-calculator.html`)** - Real-time token economics and inference cost estimator in Indian Rupees (INR) and USD across OpenAI GPT-4o, Anthropic Claude 3.5, Google Gemini 1.5, Mistral, and Groq. --- ## Key Articles & Publications Digest ### "10 Real Palantir FDE Decomposition Interview Questions (And How to Crack Them)" - *URL:* https://theneildave.in/blog/palantir-fde-decomposition-interview.html - *Core Thesis:* The Palantir Forward Deployed Engineer (FDSE) "Decomposition" round is a 45-60 minute problem-solving interview testing problem framing under ambiguity, messy legacy data ingestion, practical MVP heuristics, and operator adoption. Outlines a 4-phase whiteboard roadmap and solves 10 real production scenarios across airline fuel optimization, hospital ICU sepsis alarm fatigue, and automotive supply chain disruption. ### "The LLM System Design Interview Cheatsheet: 7 Production Architectures (2026)" - *URL:* https://theneildave.in/blog/llm-system-design-interview-cheatsheet.html - *Core Thesis:* System design interviews have shifted to non-deterministic LLM constraints: KV cache GPU memory bounds, Time-to-First-Token (TTFT < 800ms), and probabilistic drift. Provides complete whiteboard diagrams and specifications for high-throughput LLM gateways, semantic caching, hybrid RAG (Dense + BM25 + Rerank), and multi-agent state machines. ### "How to Become a Forward Deployed Engineer in 2026" - *URL:* https://theneildave.in/blog/forward-deployed-engineer-2026.html - *Core Thesis:* FDE job postings grew 729% year-over-year. The role sits at the intersection of technical scoping (60% customer-facing), integration engineering (30% production code), and internal product feedback. Palantir, OpenAI, and Anthropic have defined the standard loop around the 45-60 minute "problem decomposition" case interview. ### "Reverse Information Paradox: Protecting Enterprise AI IP" - *URL:* https://theneildave.in/blog/reverse-information-paradox-enterprise-ai.html - *Core Thesis:* Formalizes the risk where enterprise customers pay model vendors twice: once with licensing fees, and again by leaking proprietary operating procedures, prompt feedback, private evaluations, and domain heuristics into vendor telemetry. Outlines 5 architectural trust boundaries: controlling evals in-tenant, owning prompt/completion traces, isolating fine-tuning environments, decoupling orchestration from underlying model APIs, and enforcing model portability. ### "The True Cost of Running Enterprise LLMs in Production (2026 Data)" - *URL:* https://theneildave.in/blog/enterprise-llm-cost-2026.html - *Core Thesis:* Token pricing represents only 20–35% of total enterprise LLM expenditure. The remaining 65–80% stems from hidden LLMOps costs: retrieval indexing, vector database hosting, continuous evaluation pipelines, latency mitigation, retry overheads, and guardrails. ### "Agentic AI System Design: 3 Production Redesigns" - *URL:* https://theneildave.in/blog/agentic-ai-system-design.html - *Core Thesis:* Autonomous agent loops fail in production when built with open-ended planning loops. Shifting to deterministic state machines with bounded agent tool execution reduces loop failures by over 80%. ### "MCP Security: What Every Enterprise AI Architect Must Know" - *URL:* https://theneildave.in/blog/mcp-security-enterprise-ai.html - *Core Thesis:* Model Context Protocol (MCP) standardizes agent-to-tool connections but introduces new attack vectors: prompt injection via tool descriptions, unauthorized data exfiltration through unverified servers, and privilege escalation. Defines zero-trust controls for enterprise MCP servers. --- ## Contact & Knowledge Graph Verification - Website: https://theneildave.in - Wikidata URI: https://www.wikidata.org/wiki/Q138716797 - LinkedIn: https://www.linkedin.com/in/neil-dave/ - GitHub: https://github.com/theneildave/ - Google Scholar: https://scholar.google.com/citations?user=93Ybux4AAAAJ&hl=en - YouTube: https://www.youtube.com/@theneildave - Substack: https://theneildave.substack.com - Medium: https://medium.com/@theneildave - Direct Email: hello@theneildave.in - Schedule Strategy Call: https://calendly.com/theneildave