Vetted Role-Based Access Control (RBAC) Professionals

Mehrnaz AkbariQamsari

Screened ReferencesStrong rec.

Senior Frontend Developer specializing in React and TypeScript

Vancouver, BC8y exp

“Frontend engineer who led end-to-end delivery of a Next.js/TypeScript product, including a permission-based React dashboard for managing employee gift card bonuses across large companies. Demonstrated strong architecture and quality practices (multi-reviewer PR workflow), plus performance-focused UX for bulk Excel uploads using Ant Design forms with inline validation and efficient row updates. Known for close product/design collaboration to simplify complex workflows into step-based, user-friendly flows and for shipping quickly with tight QA/Jira-driven iteration.”

Nobin Johnson

Screened ReferencesStrong rec.

Mid-Level Software Engineer specializing in full-stack, cloud, and mobile development

Buffalo, NY4y exp

“Backend engineer with open-source web3.js contributions focused on preventing costly smart-contract execution failures, plus hands-on blockchain startup experience scaling an NFT mint from a test EC2 setup to AWS Lambda/API Gateway under extreme concurrency. Built a multiplayer backend improving tick rate from 40 Hz to 105 Hz using UDP, containerization, and Kubernetes, and has healthcare production support experience across 10+ apps. Also publishes IEEE research papers and produces developer-friendly documentation that accelerates team adoption.”

“Built and productionized an LLM-enhanced version of the WeDAA platform to auto-generate microservice architecture diagrams and support code generation from user prompts, including a practical solution for non-overlapping canvas object placement via coordinate templates. Experienced in diagnosing agentic workflow failures using AWS Strands agents with feature-flagged debug logging, and frequently supports sales through tailored demos and POCs to drive adoption.”

Hafiz Muhammad Zeshan

Screened

Senior Full-Stack Engineer specializing in MERN, AWS, and scalable SaaS platforms

Victoria, Australia5y exp

“Frontend lead for B2B SaaS products, owning React + TypeScript architecture end-to-end and scaling complex dashboards/workflows with a feature-based structure, shared design system (Tailwind), and strong quality automation. Experienced shipping high-impact features quickly using incremental delivery, feature-flagged rollouts, and performance profiling/optimization to keep production stable as usage grows.”

Vengalarao Pachava

Screened

Junior AI Data Engineer specializing in Azure Databricks lakehouse and GenAI RAG systems

Irving, TX2y exp

“Backend/applied AI engineer from Cloud Rack Systems who built production GenAI/RAG and data platforms on Azure/Databricks at enterprise scale (2.5M records/day). Known for making LLM systems behave like deterministic services via strict retrieval contracts, citation-based validation, and strong observability—shipping a knowledge assistant used daily by 50+ users while driving hallucinations near zero and materially improving latency and cost.”

Monish Reddy Bonthu

Screened

Mid-Level Full-Stack Engineer specializing in real-time systems and FinTech

FL, USA5y exp

“Backend engineer with hands-on experience modernizing a real-time logistics/tracking platform from a tightly coupled polling architecture to a service-oriented/microservices design using Node.js and WebSockets. Emphasizes contract-first FastAPI development, defense-in-depth security (JWT/OAuth, RLS/Supabase), and safe incremental migrations with feature flags and strong observability, delivering sub-second updates and improved performance under peak load.”

“Backend/AI engineer who built production-grade intelligence systems in high-stakes domains including tax/legal document analysis and brain tumor MRI workflows. Stands out for combining LLM/RAG product delivery with strong engineering rigor around retrieval evaluation, grounding, validation, observability, and safe fallbacks—turning impressive demos into systems users could actually trust.”

“Production-focused ML/AI engineer with hands-on ownership across classical ML and GenAI systems, from CV/NLP services to enterprise RAG. Stands out for combining research-to-production execution with measurable business impact: 40% processing-efficiency gains, 35% fewer support tickets, 5x latency improvement, and 3x throughput gains while maintaining safety and quality.”

“Built and shipped production AI search and RAG features for a university portal, including an embeddings-based semantic search layer and a documentation-grounded assistant with citations and anti-hallucination prompting. Also developed scalable, reliable data pipelines integrating Google Ads/GA4/Meta APIs for automated reporting, with strong focus on evaluation loops and retrieval quality improvements (hybrid search, chunking, query-log driven iteration).”

“Built DocMind, an end-to-end PDF chat assistant using React/TypeScript, FastAPI, and Postgres/pgvector, showing full-stack ownership plus practical performance tuning and AWS debugging skills. At Social Tech Labs, improved onboarding, shipped lean under ambiguity, and created a reusable low-latency feature serving layer that reduced duplicated infrastructure work across models.”

“Full-stack engineer who has shipped and operated generative-AI chat/QA features end-to-end, including a RAG-based pipeline with guardrails and cost/latency monitoring in production. Experienced with React/TypeScript + Node/Postgres architectures, Dockerized deployments to AWS (EC2) via GitHub Actions CI/CD, and building reliable ingestion/ETL systems with idempotency, backfills, and reconciliation.”

“Cloud/DevOps-focused engineer with hands-on experience building Azure DevOps CI/CD pipelines for containerized applications deployed to AKS, including security scanning, approvals, versioned artifacts, and rollback. Also implemented Terraform-based IaC for Azure (VNets/subnets/NSGs/AKS) with modular design, remote state/locking, and drift detection; resolved a real deployment outage caused by an Azure RBAC permission change.”