Vetted Git Professionals

Xingyu Chen

Screened

Junior Machine Learning Engineer specializing in generative AI and computer vision

Atlanta, GA1y exp

“Built production AI features for image editing and object removal, including an agent that guides users to the right pipeline, validates inputs, refines prompts, and routes requests to GPU-backed generation services. Brings hands-on experience across multimodal control, generative model optimization, and post-launch iteration driven by failure analysis and user feedback.”

“Built both traditional data infrastructure and LLM-powered product workflows, spanning a Python/SQL ETL deployment at Amazon and an adaptive learning system for their DataLingo platform. Particularly interesting for roles at the intersection of data engineering, applied AI, and customer-facing product delivery, with hands-on experience stabilizing probabilistic LLM systems in production.”

Chaithanya Konda

Screened

Mid-level Data Engineer specializing in multi-cloud analytics platforms

Waltham, MA6y exp

“Data engineer with hands-on GCP platform experience spanning BigQuery, Cloud SQL, Dataflow, and Cloud Composer, including both production operations and cloud migration work. They led a migration from legacy SQL Server/Oracle systems to a cloud-native BigQuery architecture and cite measurable impact: processing reduced from hours to minutes, query latency improved 60%+, and ingestion time improved 40%.”

“Software engineer with practical, day-to-day experience embedding AI into development workflows across coding, testing, code review, and AWS data pipelines. Uses tools like Claude, Cline, JUnit, Mockito, and Amazon Bedrock, and stands out for having a realistic, mature view of agent limitations, hallucinations, and the need for strong prompting and human validation.”

Robert Davis

Screened

Staff Software Engineer specializing in backend and distributed systems

Remote, US19y exp

“Backend engineer who co-launched SkyKick’s Office 365 SharePoint/Exchange backup product, built the MVP, and then architected and led its design for 9 years. Stands out for high-scale systems expertise, including an algorithmic redesign that cut cloud costs by an order of magnitude, plus earlier experience integrating speech recognition systems in noisy real-world customer environments.”

Ethan Hu

Screened

Entry-level Software Engineer specializing in full-stack and embedded systems

Seattle, WA1y exp

“Backend/full-stack engineer on Qualtrics' Online Samples team working on audience sampling systems and APIs used by researchers. They have hands-on ownership of TypeScript/React/Express services, emphasize multi-layer testing and production observability with Splunk/VictorOps, and have built APIs for both internal and external developers.”

“Built and deployed PIKA, an internal multi-agent platform for FDA-regulated software development, owning it from concept through production. The candidate combines strong full-stack engineering with rigorous LLM orchestration, human-in-the-loop controls, and production eval systems, delivering measurable impact: 3x more design issues caught, ~90% fewer false positives, and ~40% efficiency gains on documentation-heavy workflows.”

“Software engineer with experience spanning early-stage startup architecture and large-scale Amazon product development. They’ve driven search and data-platform decisions in a 20-person startup, built full-stack React/Python tools that automate internal workflows, and shipped marketplace expansion and personalization features impacting 200k sellers and millions of end users.”

“Built and owned an LLM support copilot at Stripe focused on improving agent ticket resolution. Designed the backend and ML system end to end, using RAG, Redis caching, hybrid vector search, and LoRA fine-tuning to achieve 40% lower latency and 22% higher response accuracy, with continuous quality monitoring via Ragas and related evaluation frameworks.”

“Built a production RAG-based "knowledge copilot" for support/ops using LangChain/LangGraph, implementing the full pipeline (ingestion, chunking, embeddings, vector DB retrieval/rerank, guarded generation with citations) and operating it as monitored microservices with CI/CD. Also designed an event-driven, streaming backend for real-time inventory ordering predictions that reduced stockouts by 25%, and has hands-on incident response experience stabilizing LLM API latency/5xx spikes using Datadog/APM and resilience patterns.”