Vetted SQL Query Optimization Professionals

Venkata Bayarapuneni

Screened

Junior Full-Stack Developer specializing in JavaScript, Python, and cloud-deployed web apps

Remote, USA1y exp

“Built and deployed a production LLM-powered travel assistant (Globe Trote) that automates end-to-end trip planning using a multi-step agent pipeline with RAG, external API calls, and enforced structured JSON outputs. Focused on reliability (validation, retries, fallback prompts, logging) and reported a ~30–40% reduction in irrelevant/generic responses after adding retrieval grounding.”

“Builder with hands-on experience shipping full-stack products across AWS cloud infrastructure, React/TypeScript apps, SQL-backed systems, and privacy-focused AI workflows. Stands out for combining cost-aware architecture, strong debugging instincts, and product thinking—from an e-commerce platform automated with IaC to a university admin portal serving 10,000+ users and a locally run AI assistant with configurable guardrails.”

“Full-stack engineer at Srasys Inc. who built and owned production payments/checkout for an e-learning platform serving 5,000+ users using Next.js App Router + TypeScript. Deep focus on correctness and reliability (Stripe webhooks, signature validation, DB-level idempotency) plus measurable performance wins (~40% latency reductions) through Postgres indexing/EXPLAIN ANALYZE and Redis-backed caching with CloudWatch monitoring.”

“Built and shipped production AI features in the automotive dealership domain, including an end-to-end computer-vision damage detection system for trade-ins and a tool-calling, RAG-enabled LotSync AI Agent that answers inventory/VIN questions using strict schemas and internal APIs to avoid hallucinations. Also developed a Dagster + Oracle automated reporting pipeline as a Graduate Research Assistant, supporting 15+ university departments with normalized, reliable ETL workflows.”

Sai Vamsee Bandaru

Screened

Entry-level Data Analyst and AI Engineer specializing in machine learning and LLM systems

New York, NY1y exp

“Founding-engineer-oriented full-stack product engineer who built an AI tutor system end-to-end, spanning React UI, FastAPI backend, retrieval/LLM pipelines, and Postgres optimization. Stands out for combining product thinking with deep systems work: improving onboarding and activation, shipping quickly with beta users, and abstracting reusable retrieval infrastructure for multiple use cases.”

Vinith Nagelly

Screened

Mid-level Full-Stack Developer specializing in Python/Django and React

Little Rock, AR4y exp

“Backend engineer at Hexanika who owned a real-time fraud-detection platform: built Django microservices, integrated a GenAI anomaly-scoring model, and optimized data/infra for low-latency production (including ~40% query-latency reduction). Experienced running containerized services on AWS/GCP with Kubernetes/GKE, GitHub Actions-based CI/CD + GitOps, and building Pub/Sub streaming pipelines and on-prem-to-cloud migrations.”

Monil Patel

Screened

Junior Software Engineer specializing in backend and cloud systems

Pennsylvania, USA2y exp

“Full-stack engineer with hands-on experience spanning analytics products and fintech infrastructure. Built a YouTube Data Aggregator end-to-end in 2025 with ingestion, dashboards, and predictive modeling, and also shipped Stripe webhook/payment systems at FinPay supporting $5M+ in transactions with 99.9% uptime.”

Niyaz Herkal

Screened

Mid Backend Engineer specializing in scalable APIs and cloud microservices

Bangalore, India3y exp

“Backend-heavy full-stack engineer who owned a high-volume booking/rescheduling system at CodeHaste, using NestJS, PostgreSQL, and advanced TypeScript patterns to eliminate double-booking issues at 10k+ daily transactions. Also co-founded KingpiN Vision Forge, where they turn ambiguous client asks into concrete web strategy and design, and has adjacent AI infrastructure experience integrating NVIDIA NIM APIs and debugging streaming issues.”

“Python backend developer from Larix Technologies who built and scaled microservice APIs for an omnichannel messaging SaaS (WhatsApp/Instagram/Facebook) and led production performance fixes during peak traffic, cutting webhook latency ~50%. Also shipped applied AI products end-to-end: a RAG-based PDF assistant (LangChain + Mixtral via Groq + React) and a BI agent that plans/executes/verifies multi-step analytics with strong guardrails and auditability.”