Vetted Full-Stack Development Professionals

“Built and shipped a map-embedding SDK (published to npm) for Walmart apps, solving key performance issues with real-time streaming (WebSockets) and Canvas rendering while prioritizing developer experience. Also applies LLM/agentic patterns in production workflows—using diagnostic agents and human-in-the-loop escalation to detect and resolve issues (e.g., voice agent loops caused by RAG API failures). Has sales-engineering experience supporting enterprise renewals, including a million-dollar contract renewal while at Siemens working with Ford stakeholders.”

“Built and productionized a multi-agent LLM analytics assistant at eBay that routes natural-language questions to retrieval or text-to-SQL, dynamically retrieves relevant schemas via a vector DB, and executes against a data warehouse. Drove a major quality lift (text-to-SQL accuracy 60%→85%) and materially reduced time engineers/PMs spent getting data insights through strong eval/monitoring, tracing, and reliability-focused design (schema retrieval, strict JSON outputs, retries/clarifications).”

“Full-stack web developer with hands-on ownership of products from requirements through launch and maintenance, building across React and Node.js. Stands out for balancing product usability with technical performance, including API/database optimizations that improved performance by about 30% and shipping real-time dashboard features with scalable frontend/backend tradeoffs.”

Alexander Smith

Screened

Junior Software Engineer and Data Scientist specializing in AI/ML systems

California, USA3y exp

“Built production-grade automation and ML/data pipelines at Dun & Bradstreet and ThreadNotion, spanning large-scale document classification, country risk report automation, and resilient Playwright testing for dynamic AI chat workflows. Particularly strong in turning brittle or ambiguous systems into reliable, observable, end-to-end automated platforms.”

Tara Munjuluri

Screened

Junior Software Engineer specializing in full-stack and AI systems

Ames, IA3y exp

“Backend-focused engineer with end-to-end ownership experience on internal platforms at John Deere, including a workforce and skills system that cut manual review time by 40%. Brings a strong reliability and compliance mindset across Java/Python microservices, AWS infrastructure, and production operations, and has also built an LLM-powered RAG system over 1M+ records with emphasis on grounded outputs and observability.”

“Backend-leaning full-stack engineer with experience at Liberty Mutual and Airbnb, building high-scale insurance claims systems (1M+ monthly transactions) and consumer booking/pricing services (120K–180K daily requests). Strong in transactional data integrity, PostgreSQL performance tuning, and production operations (Docker/Jenkins/AWS), with measurable UX/performance wins including ~2.3s page loads and significant runtime failure reduction.”

“Data/analytics engineer who built and operated a DocuSign-based real-time analytics platform end-to-end, processing 20–50k webhook events/day with ~99.5% reliability. Strong in idempotent event processing, schema-evolution-safe ingestion (raw JSON + dynamic parsing), and serving data via versioned, low-latency REST APIs with solid CI/CD and observability.”

“ML/AI engineer with hands-on ownership of production document intelligence and GenAI systems, spanning model experimentation, AWS deployment, monitoring, and iterative optimization. Stands out for turning document-heavy workflows into reliable, near real-time products with measurable gains in accuracy, latency, and manual-effort reduction, while also shipping citation-grounded RAG features that drove user trust and adoption.”

“AI engineer at Anote.ai who built and shipped a production multi-agent LangGraph/LangChain/Ray RAG platform for enterprise search and workflow automation, supporting 3 commercial products and 100+ developers. Drove measurable gains (30% accuracy improvement, lower latency) and improved reliability with Redis-based state checkpointing, message-queue synchronization, and Milvus retrieval optimizations, while partnering with PMs/clients to add transparency features like confidence scores and real-time logs.”

“Data engineer/backend developer with experience owning end-to-end, high-volume data pipelines for ML/analytics using Python, Airflow, SQL, and PySpark, reporting ~30% error reduction through improved reliability and data quality checks. Has also built Django-based REST APIs with caching/pagination and strong versioning practices, and operated external data collection/web scraping pipelines with anti-bot measures, monitoring, retries, and idempotent backfills.”

“Built and architected ML-integrated payment processing systems for PlayStation at Sony Interactive Entertainment, covering fraud determination, provider routing optimization, and model-training feedback loops in production. Brings a strong reliability and observability mindset, with concrete experience designing fallbacks, retries, correlation-ID tracing, and statistically grounded evaluation for non-deterministic systems.”

“Software engineer at Paradigm who is deeply hands-on with agentic development workflows and AI-assisted coding. He built an in-house OAuth layer to replace a third-party service and reduce projected integration costs, and also created an "ambient agent" that proactively responds to user behavior on the website. He stands out for combining full-stack architecture thinking with a disciplined, model-aware workflow for designing, implementing, and reviewing AI-generated code.”

Rucha Joshi

Screened

Junior Software Engineer specializing in full-stack and backend development

Austin, TX2y exp

“Builder of multiple zero-to-one consumer applications, including an anonymous writing feedback tool with a Gemini-powered chatbot, a dietary-profile recipe product using LLM-based substitutions, and a live-updates Sports Hub. Stands out for hands-on full-stack execution, iterative AI experimentation, and a quantified 80% reduction in time users spent finding recipe-compatible ingredients and options.”

Jiajun Huo

Screened

Mid-level Software Engineer specializing in AI, data infrastructure, and LLM systems

Urbana, IL4y exp

“Built end-to-end data and automation systems at Sonic SVM, spanning Python/FastAPI/Kafka/Spark ingestion pipelines, warehouse analytics, and Playwright automation for brittle SSO-protected dashboards. Stands out for combining backend/data engineering with strong observability and reliability practices, plus a pragmatic ability to turn messy manual business processes into measurable self-serve workflows.”