Vivek S.

Those who build intelligent product features WITHOUT modern development tooling and production-grade backend architecture usually see fragile systems and expensive rewrites. I do it differently. Clients contact me when they face below: • Their LLM feature works but isn’t stable • A RAG pipeline needs proper backend integration • An AI prototype must become production-ready • Performance and scalability issues are emerging • They need a senior engineer who can join an ongoing project and take ownership I specialize in designing and deploying Gen AI systems integrated into clean full-stack architecture. My focus is not experimentation it’s production. Core Specialization • Generative AI application development • Large Language Model (LLM) systems • Retrieval-Augmented Generation (RAG) pipelines • Agentic workflows (LangGraph-based orchestration) • Vector database integration (Pinecone, Weaviate, FAISS) • Structured output validation and evaluation systems • SaaS backend architecture • API-first full-stack engineering • AWS cloud deployment Planning & Product Structuring: • Linear • Framer AI Engineering & Implementation: • Cursor • Claude Code • GitHub Copilot • Replit Backend Architecture & API Layer: • Python • FastAPI • PostgreSQL • Supabase • Firebase • REST APIs • OpenAPI • Async Architecture Frontend & Deployment: • Tailwind CSS • Modern Component Frameworks • Vercel Cloud Infrastructure & Scalability: • AWS (S3, EC2, Lambda, App Runner, Bedrock) • Docker • CI/CD Pipelines • Multi-Tenant SaaS Architecture Monitoring & Production Reliability: • Sentry • Structured Logging • Observability Systems What I Build: • LLM-powered SaaS features • RAG-based knowledge systems • Multi-step agent workflows • Document intelligence and automation tools • AI copilots integrated into existing platforms • Full-stack SaaS platforms with Generative AI layers • Backend restructuring for AI-enabled products I work primarily with funded startups and mid-size product companies. My Typical engagements include: • Joining an active engineering team as senior backend/AI lead • Hardening LLM and RAG systems before scale • Designing full-stack architecture for new AI features • Refactoring unstable AI integrations • Leading backend modernization for SaaS products I’m comfortable stepping into ongoing projects, reviewing codebases, and stabilizing systems quickly. If you’re experimenting with AI concepts, there are many lower-cost options available. If you’re building AI-enabled SaaS features that need to handle real users, real data, and real scale senior architecture matters. I focus on long-term maintainability, measurable performance, and clean engineering. Share your current stack, your AI roadmap, and the bottlenecks you’re facing. I’ll evaluate it and propose a structured approach.