AI Solutions Architect & Full-Stack Engineer
Build Production-Ready AI Systems That Scale
Architect intelligent applications using GPT-4, Claude, Llama 3, and enterprise LLM stacks. Ship production-grade AI agents from concept to deployment in weeks, not months.
Start Your AI ProjectMeet The Developer
Bridging Cutting-Edge AI Research With Production Reality
I'm Rajesh, a full-stack AI engineer specializing in LLM development, RAG architecture, and autonomous agent systems. I transform complex AI research into robust, scalable products that deliver measurable business outcomes.
Capabilities
Enterprise-Grade AI Infrastructure
Production-hardened technology combining state-of-the-art frameworks, optimized cloud deployment, and intelligent design systems built for scale.
LLM Frameworks
LangChain & LlamaIndex ââ¬Â¢ Semantic Kernel ââ¬Â¢ AutoGen & CrewAI ââ¬Â¢ Custom Fine-tuning Pipelines
Infrastructure
Vector DBs: Pinecone, Weaviate, Chroma ââ¬Â¢ GPU Cloud: AWS, GCP, Azure ââ¬Â¢ Docker & Kubernetes ââ¬Â¢ CI/CD for LLMOps
Development
Python, PyTorch, TensorFlow ââ¬Â¢ PHP, React, Next.js ââ¬Â¢ FastAPI, Node.js ââ¬Â¢ CUDA Optimization
Development Framework
From Concept to Production in 8 Weeks
Execute AI initiatives through a battle-tested methodology delivering production systems rapidlyââ¬âwithout compromising quality, security, or scalability.
Strategic Discovery & Architecture Design
Analyze your business domain, map existing workflows, and architect optimal AI solutionsââ¬âwhether RAG systems, fine-tuned models, or multi-agent orchestration.
Rapid Prototyping & Prompt Engineering
Validate concepts within days through functional prototypes using advanced prompt engineering, few-shot learning, and chain-of-thought reasoning patterns.
Model Fine-tuning & Performance Optimization
Customize open-source models on proprietary datasets. Implement RLHF, LoRA adapters, and custom tokenization for maximum domain-specific performance.
Production Deployment & LLMOps
Launch with confidence using containerized deployments, Kubernetes orchestration, and comprehensive monitoring for LLM-specific performance metrics.
Service Offerings
AI Development Engineered for ROI
Deliver production-ready AI solutions using the latest LLM technology stack. From intelligent RAG systems to autonomous agentsââ¬âbuilt for performance, scalability, and measurable business impact.
Custom LLM Development & Fine-tuning
Train proprietary models on Llama 3, Mistral, and domain-specific datasets. Build AI that outperforms generic solutions through targeted fine-tuning and RAG integration.
Learn moreAutonomous AI Agent Architecture
Deploy autonomous agents capable of reasoning, planning, and executing complex workflowsââ¬âfrom research automation to code generation systems.
Learn moreAI-Native Interface Design
Design adaptive interfaces that predict user intent and enable natural conversation. Merge cutting-edge AI capabilities with precision-crafted user experiences.
Learn moreClient Questions
Frequently Asked Questions
Absolutely. I specialize in AI MVPs designed to scale. Multiple startup clients have secured Series A funding after shipping their intelligent product.
Engagements range from $15K for focused RAG implementations to $150K+ for comprehensive AI platforms. Fixed-price proposals provided after discovery phase.
Yes. Retainer-based LLMOps support includes model monitoring, automated retraining pipelines, and continuous performance optimization.
Ready to Deploy Production AI?
Let's Build Your Intelligent System
Join forward-thinking teams shipping AI products with custom LLMs and autonomous systems. Trusted by startups and Fortune 500 companies. Prototypes in 2 weeks. ROI-focused delivery.
Schedule a ConsultationTechnical Insights
Engineering Notes From The Trenches
Deep technical dives into LLM development patterns, RAG architecture decisions, AI agent design, and lessons learned building production AI systems.
Apr 27, 2026
How Large Language Models Decide Which Brands to Recommend
How LLMs like ChatGPT and Gemini decide which brands to mention and recommend. Covers training data bias, entity salience, retrieval-augmented answers, and what you can actually control.
Read moreApr 27, 2026
Topical Authority Explained: The #1 Factor for AI Search Visibility in 2025
What topical authority is, why it matters more for AI search visibility than any other factor, and how to build it systematically through content clusters, internal linking, and third-party signals.
Read moreApr 27, 2026
The Ultimate Guide to E-E-A-T: Making AI Search Engines Trust Your Brand
How E-E-A-T (Experience, Expertise, Authoritativeness, Trustworthiness) affects your visibility in AI search engines. Covers practical ways to strengthen each signal for both traditional and AI-powered search.
Read moreApr 27, 2026
How to Optimize for ChatGPT Search (SearchGPT): Everything You Need to Know
How to optimize your website for ChatGPT's built-in search feature. Covers how SearchGPT retrieves and cites sources, what content gets selected, and practical steps to improve your visibility in ChatGPT answers.
Read moreApr 27, 2026
Why Unlinked Brand Mentions Are the New Backlinks in the Age of AI Search
Why unlinked brand mentions now carry real weight for AI search visibility, how LLMs use entity mentions from training data, and how to build a deliberate mention strategy alongside your link building.
Read moreApr 27, 2026
Structured Data & Schema Markup: The Secret Weapon for AI Search Visibility
How structured data and schema markup improve your visibility in AI-powered search. Covers which schema types matter most, implementation examples, and how AI systems use structured data to understand your content.
Read moreApr 27, 2026
AI Search vs Traditional Search: How User Behavior Is Changing and What It Means for SEO
How AI search is changing the way users find information and what that means for your SEO strategy. Covers behavioral shifts, traffic impact, zero-click trends, and how to adapt your content for both channels.
Read moreApr 27, 2026
How to Track Your Brand's Visibility in AI Search Engines (New Metrics for 2025)
How to measure and track your brand's visibility in AI search engines like ChatGPT, Gemini, and Perplexity. Covers manual auditing, emerging tools, new metrics, and how to build a repeatable tracking process.
Read moreApr 27, 2026
The Role of Wikipedia and Wikidata in AI Brand Visibility âââ‰â¬Â And How to Leverage Them
How Wikipedia and Wikidata influence AI brand visibility, why they carry outsized weight in LLM training data, and the right way to leverage them for your brand without violating editorial policies.
Read moreApr 27, 2026
Zero-Click Search Is Here: How to Win Visibility Even When Users Don't Click
How zero-click search works, why it is growing because of AI search and featured snippets, and practical strategies to win brand visibility even when users never visit your website.
Read moreApr 27, 2026
How to Write Content That AI Systems Love to Quote and Cite
How to structure and write web content that AI search engines prefer to cite and quote. Covers answer-first formatting, quotable statements, structured data, and the content patterns that earn the most AI citations.
Read moreApr 27, 2026
Robots.txt for AI Bots: Should You Block GPTBot, PerplexityBot, and Google-Extended?
A practical guide to handling AI crawlers in robots.txt. Covers GPTBot, PerplexityBot, Google-Extended, and OAI-SearchBot with clear recommendations on what to block and what to allow.
Read moreStart The Conversation
Let's Architect Your AI Solution
Currently accepting select clients for Q2 2025. Share your project requirements and receive a technical proposal within 48 hours.
