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Vetted Audit Logging Professionals
Pre-screened and vetted.
Senior Software Engineer specializing in AI platforms, payments, and consumer systems
Senior AI Engineer specializing in LLMs, RAG, and production ML systems
Senior Python Developer specializing in FinTech and RegTech payment systems
Senior Software Engineer specializing in AI infrastructure and distributed systems
Muhammad Shoaib
Senior Site Reliability & DevOps Engineer specializing in multi-cloud Kubernetes platforms
“IBM Power/AIX infrastructure engineer who has owned large-scale Power9/AIX 7.x estates across primary/DR (VIOS/HMC/vHMC) and has deep hands-on experience with DLPAR, shared processor pool governance, and PowerHA recovery. Also brings modern DevOps/IaC capability—built Azure DevOps/GitHub CI/CD for Terraform + Kubernetes/Helm with strong security controls and resolved a production Terraform state-lock failure by redesigning backend locking and pipeline concurrency.”
Senior Software Engineer specializing in AI/ML and LLM-powered applications
Senior Software Engineer specializing in enterprise AI/LLM integration and full-stack systems
Senior Software Engineer specializing in healthcare AI and cloud platforms
Senior Full-Stack Software Engineer specializing in scalable web platforms and cloud services
Senior Full-Stack Software Engineer specializing in scalable web platforms
Andrew Stewart
Senior Software Engineer specializing in Healthcare AI and FinTech platforms
“Google Health engineer who owned and shipped an AI-powered clinical insights dashboard and NLP clinical note extraction service end-to-end (React/Next.js frontend; Python/Node microservices on GKE; TensorFlow transformers; BigQuery analytics). Demonstrated strong production rigor (CI/CD, testing, observability, guardrails for sensitive data) and delivered measurable outcomes including 30% faster diagnostics, 40% less manual documentation, 15% higher adoption, and 25% lower ops costs.”
Staff Full-Stack Software Engineer specializing in distributed systems and healthcare platforms
Staff Software Engineer specializing in enterprise SaaS billing, telemetry, and security
Senior Full-Stack Software Engineer specializing in web platforms and AI/ML-enabled services
Senior Full-Stack Python Engineer specializing in cloud microservices and AI/LLM systems
Senior Software Engineer specializing in telehealth and e-commerce platforms
Senior Full-Stack Engineer specializing in React/TypeScript, React Native, and LLM-enabled products
Staff Software Engineer specializing in secure cloud-native data platforms
Yutao Liu
Senior Software Engineer specializing in backend services and full-stack web platforms
“Project lead who partners with PM and customers to gather requirements, adjust project plans, and deliver new functionality that drives customer satisfaction and revenue. Has experience building features end-to-end and presenting successful technical demos to engineering and management audiences; no stated experience with LLM/agentic systems.”
Kalyani Chittipolu
Mid-level Data Engineer specializing in AI/ML platforms and cloud data pipelines
“Built and shipped an LLM-powered data quality assistant that generates maintainable validation checks from metadata while executing validations via Great Expectations, exposed through FastAPI and integrated into Airflow-managed pipelines. Emphasizes production reliability (structured outputs, guardrails, monitoring, versioning, human review) and works closely with compliance/operations teams to deliver clear, auditable, user-friendly AI outputs.”
Chengzhu He
Staff/Principal Cloud Infrastructure Engineer specializing in Kubernetes and OpenStack
“Platform/backend engineer focused on Kubernetes at scale: built a Java control-plane service for multi-region cluster provisioning/monitoring/upgrades using Kafka-driven async workers, and solved peak-load provisioning failures by eliminating blocking I/O and dynamically scaling consumers. Also shipped an LLM-assisted Kubernetes troubleshooting/remediation feature that pulls Prometheus logs/metrics into prompts and uses guardrails (confidence thresholds + human-in-the-loop) to prevent risky actions.”