Vetted Web Scraping Professionals

“Built and shipped open-source LLM/RAG systems, including a generative AI assistant grounded on ~30,000 scraped university web pages, improving response accuracy ~30% by moving from TF-IDF-only retrieval to a hybrid sentence-transformer approach with fallback controls. Also partnered with non-technical leadership at Securi.ai to deliver real-time predictive analytics dashboards (Elasticsearch + Jira/ServiceNow) that reduced project overhead by 18%.”

“Software engineer focused on reliability and scalable systems: built React/TypeScript dashboards backed by Java/Spring Boot APIs and designed Kafka-based microservices with strong contract/versioning discipline. Known for shipping incremental improvements with tight feedback loops and for creating internal observability tools that streamline on-call and incident diagnosis under high-traffic conditions.”

“Robotics-focused Python developer who built autonomous navigation for a differential-drive robot using onboard vision and AprilTag detection, including pose estimation and coordinate frame transformations for localization and motion planning. Also has practical backend performance experience using Redis TTL caching to speed responses and reduce server load, plus basic PostgreSQL query/index optimization.”

Shriya Bannikop

Screened

Mid-level Software Engineer specializing in cloud platforms, data engineering, and distributed systems

Seattle, WA5y exp

“Full-stack engineer who built and owned an AI-assisted job-matching dashboard in Next.js App Router/TypeScript, keeping LLM logic server-side and improving performance via deduplication, caching/revalidation, and streaming (35% fewer duplicate LLM calls; 40% faster first render). Also has strong data/backend chops: designed Postgres models and optimized queries at million-record scale (1.8s to 120ms) and built durable AWS multi-region telemetry workflows with idempotency, retries, and monitoring.”

“Data engineer with experience at Expedia building SQL Server and Azure Data Factory pipelines for business reporting and analytics. Stands out for pragmatic end-to-end pipeline ownership in ambiguous environments, with a strong emphasis on data quality, rerunnability, query performance, and making downstream datasets reliable for other teams.”

“Undergraduate robotics researcher who built a crowd-aware motion planning system to navigate safely and efficiently through dynamic pedestrian environments, implementing the full pipeline in ROS (move_base, global planning, SLAM/localization) and validating via 2D crowd simulation. Also brings modern software delivery experience from web apps, including Docker/Kubernetes-based cloud deployment and CI/CD with automated testing.”

“Backend/data engineer with hands-on production experience across FastAPI/PostgreSQL APIs and AWS (Lambda, ECS) delivered via Terraform + GitHub Actions. Built Glue-based ETL pipelines into Redshift with schema evolution and data quality checks, modernized legacy reporting into Python microservices, and has demonstrated measurable SQL performance wins (multi-second query reduced to sub-300ms).”

“Analytics-focused candidate with hands-on experience building SQL reporting tables from messy transactional and master data, plus Python workflows that automate monthly analysis and data checks. They appear strongest in KPI/reporting ownership, metric standardization, and stakeholder alignment, with examples of improving reporting consistency, surfacing issues earlier, and reducing manual reconciliation effort.”