Vetted Web Scraping Professionals

“Software developer with EdPlus experience building pragmatic internal tools (Next.js/TypeScript) and cloud automations (AWS) that feed Google Sheets and Looker Studio dashboards for operational visibility across 30+ student workers. Also worked on an IEEE Xplore-published missing-person tracker using a SPARQL graph database on Azure with a TypeScript/React frontend, and has experience navigating legacy access constraints (OpenVPN) while enabling remote VR previews via ngrok.”

“Built and shipped a production LLM-powered decision system that replaced a slow, inconsistent manual review process by turning messy text into structured, auditable outputs behind an API. Demonstrates strong end-to-end ownership of reliability and operations (schema validation, retries/fallbacks, latency/cost controls, monitoring for drift) and a disciplined approach to evaluation and regression testing. Experienced collaborating with non-technical reviewers to define success criteria and deliver interpretable outputs that get adopted.”

“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.”

“Full-stack AI engineer who built Skillmatch AI, an LLM/RAG-based job matching platform using FastAPI microservices, Airflow-orchestrated async pipelines, and Pinecone vector search (sub-second retrieval across 50k+ vectors) deployed on GCP with autoscaling. Also partnered directly with a cancer researcher to automate SEER + PubMed-driven report generation via an AI pipeline, emphasizing rapid prototyping and outcome-focused communication.”

“Backend developer (recent co-op at Ticker) building and architecting financial backend services with near real-time data needs, including third-party API integrations. Improved performance and reliability via Redis caching (tiered refresh + TTL) and PostgreSQL query tuning (EXPLAIN ANALYZE + composite indexes), and has exposure to AI-agent/RAG concepts for validating stock-market information against trusted sources.”

“Entrepreneurial product builder who has shipped two live App Store apps (Pixo content-based product marketing platform and Clutch AI dating reply helper). Also helped build a real-estate seller platform end-to-end, using AI matching to find buyers and contributing to onboarding nearly paying users and generating active MRR.”

“Backend/cloud engineer with hands-on ownership of a climate data extraction pipeline (BeautifulSoup + Pandas ETL + CRON) that automated 50k+ monthly data points and removed ~20 hours/week of manual work. Also built a multi-AZ Kubernetes deployment for a Node.js system using Terraform and GitHub Actions (blue-green, rollbacks) and has Kafka/FastAPI experience from a healthcare plan management project.”

“GenAI/LLM engineer who built and productionized a 0-1 application (EMULaiTOR at Lumanity) combining qualitative + quantitative data using Postgres/pgvector RAG and prompt engineering, deployed with Azure backend and AWS-hosted frontend. Demonstrates strong production instincts (latency reduction via region alignment, autoscaling/health checks) and hands-on agent/tool-call debugging, plus experience enabling sales and winning a large pharma client.”

“Built and shipped production LLM systems at Founderbay, including a low-latency voice agent and a graph-based multi-agent research assistant. Strong focus on reliability in real workflows—hybrid SERP + full-site scraping RAG, grounding guardrails, validation checkpoints, and transcript-driven evaluation—plus performance tuning with async FastAPI, Redis caching, and containerization. Also partnered with a non-technical ops lead to automate post-call follow-ups via call summarization, field extraction, and tool-triggered actions.”

“Frontend engineer who led end-to-end architecture for a warehouse management platform, emphasizing reusable domain-based React components and API-driven performance at scale (including barcode-scanning workflows). Also delivered a production-ready React Native iOS networking app MVP in ~5 weeks and built a data-driven React+TypeScript dashboard for collectible card market decisioning.”

“Built Meet.AI end-to-end and made concrete architecture/performance decisions (RPC with type-safe integration; SSR + query prefetching for instant data display). Also created a Python tool at Abbott to resynchronize Ansible inventories and eliminate manual intervention by scheduling it in a Jenkins pipeline; has hands-on Docker/microservices experience including serving a pretrained LLM.”

“Backend engineer with legal-tech and AI workflow experience: built JurisAI, an end-to-end legal research system using OCR + embeddings + Pinecone vector search to deliver citation-grounded LLM answers with safe failure modes (~90% recall@K). Also led a GW Law metadata migration into Caspio with batch validation and parallel rollout, and has strong FastAPI/GCP production reliability and observability practices.”

“Built a production Apple-focused LLM Q&A bot that answers user issues using similar past discussion records, including large-scale scraping and cleaning of thousands of forum threads. Used BeautifulSoup + Playwright for static/dynamic extraction, PySpark + NLP for preprocessing, and LangChain RAG with a custom response-likeliness metric to evaluate performance.”

“Full-stack TypeScript/React/Next.js builder who created an end-to-end customer-facing product (AI Job Master) that generates personalized outreach from resumes and job descriptions. Demonstrates strong product + engineering ownership with rapid MVP iteration, instrumentation-driven prioritization, and pragmatic reliability patterns (microservices, queues, correlation IDs, retries) while tackling a key AI challenge: user trust and output consistency.”

“Backend Python engineer with end-to-end ownership of secure financial data systems integrating banking/credit/payment platforms, including automated ingestion and reconciliation of large financial statements. Built modular Dockerized Django REST services with pandas-driven validation/normalization and Postgres/Mongo persistence, and supported a phased migration from legacy VM services to AWS containers with stateless refactors and parallel-run integrity checks (run IDs/checksums). Works closely with platform teams on GitOps/CI readiness and deployment coordination (e.g., ArgoCD-managed sync policies).”

“Backend/Python engineer focused on real-time sensor/IoT analytics: built dashboards and a high-throughput ingestion pipeline (MQTT -> Python worker -> TimescaleDB) with buffering, batch inserts, and validation. Strong Kubernetes + GitOps practitioner (Dockerized microservices, HPA, probes, ArgoCD) who has handled production incidents like CrashLoopBackOff under peak load and supported an on-prem analytics migration to AWS using shadow traffic and rollback plans.”

“Built and productionized a RAG-based semantic search system for video-derived data, focusing on measurable success metrics (p95 latency, reliability, cost/request) and strong observability (prompt versions, retrieved docs, tool calls, token usage). Experienced in diagnosing real-time issues in LLM/agentic workflows and in supporting go-to-market efforts through tailored technical demos, rapid POCs, and post-close onboarding.”