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 • Semantic Kernel • AutoGen & CrewAI • Custom Fine-tuning Pipelines
Infrastructure
Vector DBs: Pinecone, Weaviate, Chroma • GPU Cloud: AWS, GCP, Azure • Docker & Kubernetes • CI/CD for LLMOps
Development
Python, PyTorch, TensorFlow • PHP, React, Next.js • FastAPI, Node.js • CUDA Optimization
Development Framework
From Concept to Production in 8 Weeks
Execute AI initiatives through a battle-tested methodology delivering production systems rapidly—without compromising quality, security, or scalability.
Strategic Discovery & Architecture Design
Analyze your business domain, map existing workflows, and architect optimal AI solutions—whether 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 agents—built for performance, scalability, and measurable business impact.
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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.
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Autonomous AI Agent Architecture
Deploy autonomous agents capable of reasoning, planning, and executing complex workflows—from research automation to code generation systems.
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AI-Native Interface Design
Design adaptive interfaces that predict user intent and enable natural conversation. Merge cutting-edge AI capabilities with precision-crafted user experiences.
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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.
Building a Production RAG System: From 10ms to 100ms Latency
In this deep-dive tutorial, I'll show you how I built a production RAG system that handles 1M+ documents with
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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.