Vetted Full-Stack Development Professionals

“Backend/data engineer focused on climate/emissions data platforms, building production Python (FastAPI) microservices and AWS serverless/ETL pipelines (Glue/Athena/Lambda/EventBridge). Demonstrated strong reliability and observability practices plus measurable optimization wins, including cutting PostgreSQL query runtimes from minutes to seconds and reducing AWS costs from ~$6k/month to ~$400/month.”

“Application-focused engineer who has shipped end-to-end products across mobile and web, including a music-based dating app feature for sending searchable/previewable songs in chat and a geospatial events service integrating external APIs. Demonstrates strong product + engineering instincts: performance-minded PostgreSQL modeling, Dockerized deployments with env-based config, and UX/accessibility polish backed by user studies, plus hands-on incident mitigation using Vercel logs.”

“Full-stack system analyst/programmer at PeakPlay Sports (startup) who built an AI "coach" product end-to-end in ~2 months, using a LangGraph-orchestrated multi-agent architecture with a FastAPI backend. Shipped production RAG grounded in athlete history (OpenAI embeddings + vector store) with guardrails and a structured eval loop (golden set + LLM-judge + human review) to improve engagement and reduce hallucinations.”

Esther Jibrin

Screened

Junior Software Engineer specializing in Python, SQL, and technical support

Calgary, Canada3y exp

“Frontend-focused early-career developer who led a student club web app from stakeholder discovery and Figma UX/UI through a scalable React + TypeScript build, emphasizing accessibility, reusable components, and tight API alignment with backend. Also has freelance experience translating non-technical client needs into polished sites (including Wix) and has refactored/optimized an existing codebase for maintainability and performance.”

Dhwani Patel

Screened

Mid-level Full-Stack Python Developer specializing in AI/ML and backend APIs

BC, Canada15y exp

“Python/Django backend engineer with open-source experience upgrading Archivematica to Django 4.2 LTS, including resolving a tricky breaking change in datetime parsing by implementing a preservation-safe legacy timestamp conversion layer. Also built a cost-efficient, reproducible Small Language Model (Microsoft Phi-3) fine-tuning pipeline that turns CSV product data into a domain-specific searchable Q&A chatbot, with emphasis on memory optimization and overfitting prevention.”

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.”

“Built end-to-end product features for a Web3 monetization platform and also shipped a privacy-first mobile accessibility app, SenScribe, using on-device sound classification and LLM summarization with zero cloud dependency. Particularly interesting for roles spanning full-stack product engineering, mobile AI, and applied ML where careful debugging, stakeholder alignment, and real-world usability matter.”

SaiDheerajReddy Gadikota

Screened

Mid-level AI Engineer specializing in agentic systems and enterprise LLM platforms

USA, USA4y exp

“Current AI engineer at a startup who has spent the last year architecting multi-agent systems for software development workflows. Stands out for combining LLM speed with engineering discipline—using tools like Pydantic, LangGraph, and LangChain to build reliable, production-ready agent workflows with validation, routing, and retry logic.”

“Frontend engineer focused on scalable React + TypeScript dashboards and workflows, using feature-based architecture and a reusable component/hook approach. Has hands-on experience improving performance in table-heavy admin UIs (pagination, lazy loading) and shipping major features quickly with staging/manual QA, gradual rollouts, and rapid iteration based on production feedback.”

“Software engineering intern who built and deployed a full-stack telemedicine platform (React/Node/MongoDB) used daily in a pediatric clinic, incorporating PyTorch-based predictive features. Demonstrated strong customer-facing iteration and production performance debugging—resolved a live slowdown by indexing/optimizing MongoDB queries and adding caching, improving response times by ~50%.”

Yousef Abdelsalam

Screened

Junior Software Engineer specializing in Odoo, web performance, and backend systems

Orlando, FL2y exp

“Full-stack developer who shipped LLM-powered customer support automation, including an AI call center designed for always-on, high-concurrency real-time phone handling. Also built a WhatsApp lead-conversion chatbot using Zapier webhooks, Redis state, and Twilio messaging, and reports measurable outcomes (+11% customer satisfaction, ~7% cost reduction) while using GPT-4.1.”

Ayushant Khandekar

Screened

Junior Full-Stack Developer specializing in GenAI-powered web and mobile apps

Remote2y exp

“Web3 creator-led growth and community builder who frames crypto as infrastructure and designs content to drive measurable on-chain behavior. Uses X-native distribution (threads, replies, quote-tweets) paired with interactive CTAs and on-chain dashboards to convert attention into trust and product usage, with a structured 90-day plan for launching and scaling protocol communities.”

“Unity/C# gameplay and rendering engineer who built a custom per-object shadow system in URP that improved performance from roughly 30 FPS to 80+ FPS while preserving high-quality dynamic shadows. Also built a personal multi-process AI/LLM workflow platform with custom prompt/control protocols, streaming UX, and cost-optimized memory/caching architecture—showing unusual depth across both real-time graphics and applied AI tooling.”

Citlalli Trejo

Screened

Entry-level Full-Stack Developer specializing in web, iOS, and ML applications

Buena Park, CA1y exp

“Builder-minded software engineer who has shipped a live iOS budgeting app and a solo full-stack web app, with strong evidence of production discipline in both ML and fintech-style integrations. Particularly compelling for roles involving ambiguous product problems, third-party API reliability, and end-to-end ownership from backend logic through user-facing recovery flows.”

“Early-career software engineer who has already owned a real-world web product end-to-end for a 100+ member university ACM organization, including requirements gathering, UI/UX improvements, hosting, CI/CD, and ongoing maintenance. Brings hands-on React and full-stack project experience with a strong bias toward practical execution, mobile-friendly design, and reliable delivery.”

“Built and shipped a production AI assistant for a web-based loan/interest calculator that helped users understand EMI results and optimize inputs. Demonstrated full-stack ownership across responsive UI, Node.js APIs, and LLM integration, with a strong focus on prompt refinement, guardrails, caching, fallbacks, and post-launch iteration driven by logs and user behavior.”

eman akram

Screened

Junior Full-Stack Developer specializing in AI/ML and mobile/web apps

Wah Cantt, Pakistan2y exp

“Built an end-to-end car maintenance application from design through deployment using TypeScript/React with a Node.js + Firebase backend, including OBD integration. Uses mock servers and a layered frontend architecture (UI/state/services separation) to iterate quickly on UX without being blocked by backend or hardware dependencies.”

“Internship-built full-stack systems spanning HR employee-record portals and internal data-quality dashboards (Flask + SQL + React), emphasizing data integrity and rapid MVP iteration. Also implemented Flask microservices with RabbitMQ for distributed task processing, addressing duplication/ordering issues with idempotency, durable queues, and correlation-ID logging; delivered quantified productivity gains for HR teams.”