Vetted Audit Logging Professionals

“Built a production GenAI support agent at Amazon for FBA on-call operations, using Bedrock, Lambda, RAG, and confidence-based human fallback to safely automate ticket triage. The system materially reduced ticket volume and manual workload while improving MTTR, showing strong depth in reliable LLM agent architecture under real operational constraints.”

Tara Munjuluri

Screened

Junior Software Engineer specializing in full-stack and AI systems

Ames, IA3y exp

“Backend-focused engineer with end-to-end ownership experience on internal platforms at John Deere, including a workforce and skills system that cut manual review time by 40%. Brings a strong reliability and compliance mindset across Java/Python microservices, AWS infrastructure, and production operations, and has also built an LLM-powered RAG system over 1M+ records with emphasis on grounded outputs and observability.”

Timothy Chu

Screened

Senior Software Engineer specializing in backend systems and data pipelines

Atlanta, GA11y exp

“Backend-leaning full-stack engineer from Home Depot who operated in small, startup-like teams with end-to-end ownership of critical production systems. Stands out for combining Go/Python backend depth, React/TypeScript collaboration, and strong reliability instincts—improving search latency by 40%, cutting DB latency by 35%, and hardening high-volume data and compliance pipelines.”

“Backend/full-stack engineer (5+ years) with Shopify experience integrating LLM/RAG workflows into production APIs. Owned a Python TensorFlow Serving inference pipeline connected to Java microservices via gRPC, optimizing tail latency at ~10k concurrent load and improving retrieval relevance with embedding and evaluation work. Strong Kubernetes/EKS + GitOps/CI/CD background, including monolith-to-microservices migrations and event-driven streaming patterns.”

Hansraj Pabbati

Screened

Senior Software Engineer specializing in AI/LLM systems and cloud backend platforms

Remote, CA8y exp

“Built and owned an end-to-end AI-powered natural-language-to-SQL deployment within Oracle OCI/Autonomous Database, including enrichment pipelines, RAG-based retrieval, SQL generation APIs, and post-launch monitoring. Stands out for combining LLM production engineering with strong guardrails, stakeholder management, and operational rigor around accuracy, latency, hallucination mitigation, and reliability.”

“Senior full-stack engineer with seed-stage fintech experience who has led payment API development, implemented compliance-related standards, and built production systems across React, Go, Python, Node.js, and PostgreSQL. Notable impact includes enabling a first major client launch, reducing logistics response times by 30%, improving page load times by 40%+, and cutting analytics report generation from minutes to seconds.”

“Full-stack engineer with strong AI systems and B2B SaaS experience across BrightOps, Zapier, Nordstrom, and Calendly. They’ve owned architecture for an AI-powered tutoring platform, improved retrieval quality with a hybrid vector-plus-keyword approach, and built Go services processing over 1 million student events per day. Particularly compelling for teams building data-intensive, reliability-critical products with LLM, workflow automation, or compliance-oriented use cases.”

“Built and shipped customer-facing AI systems in banking, including an AI fraud support workflow and virtual assistant at Citi/Citibank that handled over 1 million conversations per month. Combines full-stack engineering, LLM/RAG architecture, and strong compliance-minded design with PII masking, audit logging, confidence thresholds, and human escalation for regulated environments.”