Vetted HTML Professionals

Naisarg Halvadiya

Screened

Senior Full-Stack & AI Engineer specializing in scalable web platforms and LLM automation

Bengaluru, India4y exp

“Built a production agentic AI assistant in Python using Playwright plus Google Gemini’s vision capabilities to automatically document and execute UI workflows step-by-step, reducing developer time spent on trivial documentation/knowledge transfer. Also built an Apache Airflow ETL pipeline and has experience evaluating AI agents with human-in-the-loop methods, plus successfully communicated a vision-model-based CMS analytics PoC to non-technical university stakeholders and proposed it to Academic Technology with cost-savings rationale.”

Yang Qi

Screened

Mid-level Full-Stack Software Engineer specializing in AI platforms and data visualization

Cambridge, MA3y exp

“Full-stack engineer with healthcare/bioinformatics experience who built a real-time genomic data analysis and 2D visualization feature (React/TypeScript + D3, FastAPI) at University of Utah Health, deploying on AWS ECS Fargate with monitoring and measuring engagement via Google Analytics. Also built AWS Lambda-based ETL pipelines for lab data ingestion using pandas/NumPy with reliability patterns (idempotency, retries, CloudWatch alerting) and drove maintainability improvements through shared component libraries and React hooks.”

Sai Srujan Vemula

Screened

Mid-level Full-Stack Developer specializing in Java/Spring Boot and React on AWS

CT, USA3y exp

“Full-stack engineer with enterprise experience at Meta System and DXC, owning end-to-end delivery of a shipment visibility portal (React UI in Liferay DXP + Java/Spring Boot REST APIs) with Dockerized deployments and automated test coverage. Has hands-on AWS work across EC2/Lambda/S3 and multiple databases (DynamoDB, RDS, Neptune, DocumentDB), plus built a Python/Flask data migration platform with validation for correctness and repeatability.”

“Healthcare-focused ML/AI engineer who has built clinical note summarization and medical image annotation solutions using LLMs, RAG, and multimodal models. They combine experimentation across major model providers with practical production concerns like monitoring, drift detection, and latency/cost tradeoffs, and also earned 2nd place in a Google hackathon for a medical AI assistant.”

Sai Prudhivi

Screened

Mid Software Engineer specializing in full-stack microservices and cloud platforms

New York, NY4y exp

“Backend-focused engineer with experience building high-volume policy management and enterprise pricing systems, including Django/FastAPI/Flask services, Kafka-based async workflows, and Prometheus/Grafana observability. While they have not yet shipped a customer-facing AI agent or production LLM integration, they bring strong cloud, API, reliability, and scalable system design fundamentals that translate well to responsible AI infrastructure work.”

“Built and launched a production AI knowledge assistant at Virtusa used by 8,000 people, combining RAG, tool use, and strong reliability practices to cut lookup time by 60%. Also owns full-stack delivery, including a real-time transaction monitoring dashboard built with React, Spring Boot, and Kafka handling 200K API requests per day.”

“Software engineer currently building for a wealth management platform, with hands-on ownership across React/TypeScript front ends, Azure serverless backends, and SQL data systems. Stands out for turning hackweek concepts into production features, building observability infrastructure from scratch, and delivering measurable gains in latency, uptime, incident response, and client satisfaction.”

Shrey Patel

Screened

Junior Software Engineer specializing in AI-driven backend and full-stack systems

New Brunswick, NJ2y exp

“Full-stack AI engineer who has built both a healthcare voice-feedback system for Rutgers Health and an LLM-powered meme generation pipeline at Attention.ad. Stands out for combining React/TypeScript, FastAPI, Postgres, real-time systems, and frontier-model orchestration with practical product instincts, including measurable latency/cost improvements and strong iteration based on user feedback.”

“Software engineer with startup experience building finance ERP features across invoices, billing, tax updates, and bank reconciliation, now pivoting toward AI/ML through an ML internship and hands-on NLP projects. Brings a mix of full-stack product exposure, early-stage comfort, and practical experimentation with BERTopic, HDBSCAN, LangChain, MongoDB vector search, and sentiment modeling.”

“Early-career backend/data engineer with experience spanning university operations and banking systems. They’ve owned a Python-based automation that replaced manual alumni data maintenance at Georgia State University, cutting effort by 85% and centralizing 280+ profiles, and also worked on Java/Spring Boot services for legacy banking reconciliation and reusable multi-workflow APIs.”

“Full-stack software engineer who shipped production systems in academic and e-commerce contexts, including a UC Irvine course recommendation platform with async Kafka-based OCR processing (Tesseract) and LangChain-driven recommendations. Strong in building polished React/TypeScript dashboards (Figma-to-implementation) and owning Python backends (FastAPI/Flask) with solid API design, caching, and AWS EKS deployments; delivered measurable impact (tripled engagement, ~50% faster processing).”

“Full-stack engineer who built an early-stage social platform for scriptwriters (Scriptscape) from scratch, owning everything from React Native/React UX to Node/Postgres APIs and AWS deployment. Demonstrates strong production-minded engineering with CI/CD, observability, and scalability patterns (cursor pagination, indexing, background jobs), plus experience hardening flaky third-party integrations with idempotency and backfills.”

“Backend engineer with fintech/AI startup experience who built an Azure serverless, event-driven pipeline for large-scale crypto sentiment analysis and semantic search (OCR/NLP to vector search) and integrated LLM + blockchain data for predictive insights. Demonstrated measurable impact (25% lower retrieval latency, 10% fewer data errors, 15% higher engagement) and has led safe microservices migrations with strong security and reliability practices.”

“Research assistant who single-handedly built and integrated an indoor autonomous wheelchair system using NVIDIA Jetson Nano, LiDAR, and a stereo camera. Implemented a multi-sensor perception pipeline (OpenCV/PCL) with ROS-based modular nodes, TF frame management, and robust debugging via RViz/rosbag, plus simulation testing in Gazebo and Dockerized environments for portability.”

“AI Engineer at Humanitarian AI who has built and productionized both a LangGraph-based multi-agent workflow system and a RAG pipeline (OpenAI embeddings + vector DB) with rigorous evaluation/guardrails. Reports strong measurable impact (60% faster workflow delivery, 40% fewer incidents, 70% reduced research time) and has prior enterprise modernization experience at Infosys migrating ETL to microservices with zero production incidents.”

“Backend engineer who has designed and evolved high-traffic event/activity management systems using Node/Express and PostgreSQL, prioritizing scalability and reliability with a layered architecture. Has led zero-downtime refactors/migrations using parallel runs, dual writes, and rigorous validation/monitoring, and brings a security-focused API approach (JWT, RBAC/ABAC, rate limiting, DB-enforced tenant/RLS filters).”

“Backend/data engineer with strong production experience across Python microservices (FastAPI) and AWS serverless/data platforms (Lambda, API Gateway, Glue, Redshift). Demonstrates reliability and incident ownership (rate limits, retries/circuit breakers, monitoring) and has delivered measurable SQL performance gains (12–15s to <800ms, ~60% CPU reduction). Seeking fully remote work and not open to relocation/onsite meetings.”

“Backend engineer with deep experience modernizing a provider credentialing/compliance platform with multiple upstream/downstream integrations. Focused on building predictable, scalable REST APIs (primarily ASP.NET Core; framework-agnostic approach applicable to FastAPI), improving performance via DB/query optimization, and hardening workflows with idempotency, transactions, feature flags, and strong auth/RBAC patterns.”

“Backend/data engineer with hands-on AWS serverless and data platform experience: built a Lambda-based reCAPTCHA/token validation + SES subscription workflow and designed Glue ETL pipelines producing Parquet datasets for Athena. Also led a high-traffic multilingual media CMS modernization at Radio Free Asia by migrating to Arc XP using parallel runs, phased rollouts, feature flags, and rollback plans.”

“Frontend engineer who led end-to-end delivery of a customer-facing ticket booking platform at Simplii Financial, emphasizing scalable React architecture, performance (code-splitting/lazy loading), and accessibility. Also built a data-heavy real-time metrics dashboard at Q-TED using React + TypeScript with React Query for server-state, strong API contract validation practices, and tight QA/product/design collaboration for fast, stable releases.”

“Engineer with experience in regulated healthcare and financial systems, including a United Health healthcare service migration to AWS. Built documentation-as-code for CI/CD (Jenkins/Docker/Kubernetes/Terraform + GitHub Actions) that accelerated release cycles from 3 weeks to 4 days and tied security configuration (Spring Security/OAuth2/JWT) directly to HIPAA/GDPR compliance. Strong in observability-led incident response (ELK/Prometheus/Grafana) and performance tuning (PostgreSQL, async processing), citing MTTR reduction from 3 hours to 50 minutes and support for 250K+ concurrent users.”

“Product/UX designer with experience digitizing Penske trucking operations and Ridecell fleet lifecycle/workshop orchestration systems. Designs complex, high-liability industrial workflows using a state-driven interaction model and a calm, high-clarity visual language, backed by targeted field research with drivers and ops teams and strong collaboration with engineers (React/Tailwind, Storybook, code-linked prototypes).”

“Accenture engineer who built and shipped a production RAG-based automation/chatbot for SAP incident triage and troubleshooting, embedding thousands of runbooks/logs/tickets into a semantic search pipeline and integrating it into Teams/Slack. Reported major productivity gains (30–60% time reduction), >90% validated answer accuracy, and sub-2-second responses, with strong orchestration (Airflow/Prefect/LangGraph) and reliability practices (guardrails, testing, monitoring).”