Vetted CI/CD Professionals

“Senior engineering leader with a rare blend of deep platform/infrastructure expertise and large-scale people leadership, spanning hands-on cloud-native architecture through management of globally distributed organizations of up to roughly 180 engineers. Particularly strong in Kubernetes platform modernization, reliability engineering, and scaling high-throughput SaaS systems while aligning platform investments to customer and business outcomes.”

Xun He

Screened

Staff Software Engineer specializing in backend systems and security engineering

25y exp

“Senior backend/infrastructure engineer with experience at Microsoft, DocuSign, Pinterest, and Harness, focused on security and developer productivity systems. Stands out for building Pinterest's first vulnerability management platform from scratch for a 100,000-EC2 production environment and driving major performance gains, while also delivering CI/Docker infrastructure and Python test intelligence features shaped by customer demand.”

Pavithra Kollu

Screened

Mid-level Machine Learning Engineer specializing in LLMs, RAG, and search systems

San Francisco, CA5y exp

“Backend/ML infrastructure engineer with experience at Perplexity and Meta building production evaluation, monitoring, and retrieval systems for AI search, autonomous agents, and LLM-powered workflows. Particularly strong in turning messy manual quality-review processes into reusable Python/FastAPI automation with measurable impact, including major gains in search relevance, latency, and grounded answer quality.”

“AI/LLM engineer with production experience at NVIDIA and Microsoft, including building a RAG-based enterprise knowledge assistant that improved accuracy by 42% and scaled to thousands of queries. Deep in inference optimization (TensorRT-LLM, Triton, quantization, speculative decoding) and MLOps/observability (Prometheus/Grafana, MLflow, LangSmith), plus orchestration with Kubeflow/Airflow across multi-cloud.”

Yishi Wang

Screened

Junior Machine Learning & Data Science professional specializing in LLMs and analytics

Chicago, IL3y exp

“Amazon internship experience building production GenAI analytics for the returns organization: a multi-agent LLM+RAG system that let analysts query multiple heterogeneous data sources in natural language without hand-written SQL. Also built and operationalized four Apache Airflow DAGs for large-scale ETL, emphasizing observability and freshness-aware metadata to keep outputs accurate and up to date.”

“Engineering leader with a mix of large-scale platform experience at Microsoft and product/customer-facing work across GM, Panasonic, Acuity, and other environments. Stands out for combining people leadership with hands-on depth in accessibility, web performance at 120M+ MAU scale, and cross-functional delivery spanning enterprise permissions, e-commerce, AI, and automotive systems.”

Vinay Ramrupe

Screened

Mid-level AI/ML Engineer specializing in LLM and enterprise generative AI

San Francisco, CA5y exp

“ML/AI engineer focused on taking LLM systems from experimentation to reliable production, including enterprise copilot and RAG-based knowledge retrieval use cases. Stands out for combining data pipelines, model training, inference optimization, automated evaluation, and safety guardrails, with cited impact including 20% throughput gains and 30% less manual evaluation effort.”

“Seasoned business leader with decades of leadership experience (including Fortune 50/500) and prior Silicon Valley startup exposure, now pursuing entrepreneurship. Building “Datascension,” a gamified, story/episode-based career coaching platform that includes hands-on tasks (e.g., SQL queries, Python scripts) plus a participation-based credit/currency system and certification/badging, informed by feedback from recruiters and coaching/recruiting firms.”

“Hands-on engineering manager on a large web product who built an AI-driven navigation search and led a major post-acquisition unification effort across 3 companies and 5–7 teams, including front-end architecture for 60+ developers. Also owns a high-scale BFF (800 endpoints) and drove a deep reliability fix involving Kubernetes/Envoy/Redis session bloat, adding monitoring and preventative controls.”