Vetted Cloud Computing Professionals

“Built a production-grade LLM evaluation and regression system that stress-tests models across hundreds of iterations, combining LLM-as-judge, semantic similarity, statistical metrics, and rule-based checks, with results delivered via stakeholder-friendly HTML reports and dashboards. Experienced orchestrating multi-agent RAG workflows using LangChain/LangGraph and event-driven GenAI pipelines in n8n integrating OCR, speech-to-text, and external APIs, with strong emphasis on reliability, observability, and explainable failures.”

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.”

“Backend/AI engineer who built Matchable, an end-to-end AI-powered workforce matching platform using FastAPI, transformer-based NLP, PostgreSQL, and AWS, with a strong focus on practical system design tradeoffs. Also brings research-oriented experience from Los Alamos/ASU simulation work and has built multi-agent LLM workflows with schema validation and auditability, suggesting a thoughtful approach to reliability in AI systems.”

Sanskar Pandey

Screened

Junior Full-Stack Java Developer specializing in FinTech microservices

OH, USA3y exp

“Full-stack engineer with production experience building a real-time order tracking system using React + Firebase/Firestore, emphasizing audit-friendly data modeling, state-machine-based status transitions, and strong post-launch ownership (performance, security rules, reliability). Demonstrated measurable frontend performance gains by isolating real-time updates to dynamic components and applying memoization, plus backend reliability patterns (idempotency, retries) and SQL query/index optimization validated with EXPLAIN ANALYZE.”

Pranav Mishra

Screened

Junior Machine Learning Engineer specializing in LLM agents, RAG, and MLOps

Charlotte, NC2y exp

“AI/ML engineer who has shipped production systems across computer vision and conversational agents: built a YOLOv8-based wheel fitment pipeline at a Techstars-backed automotive startup, focusing on sub-second latency, monitoring, and robust fallback mechanisms that drove 2–3x page view growth and +5–6k users. Also built a voice-based interview platform orchestrating Deepgram + GPT-4 Mini + OpenAI TTS with FSM-driven reliability, and has hands-on RAG experience (LangChain, hybrid retrieval, cross-encoder reranking, custom pseudo-query generation).”

Rethvick Sriram Yugendra Babu

Screened

Junior AI/ML Software Engineer specializing in Generative AI and scalable data pipelines

Tucson, AZ2y exp

“Built and operated large-scale biodiversity/ecological research platforms, integrating 50+ heterogeneous global datasets into a unified BIEN 3 schema on PostgreSQL/PostGIS and improving data consistency by 35%. Strong production engineering background (Linux monitoring, CI/CD performance gates, Docker on AWS/Azure) plus applied AI work building a Python RAG system (0.90 precision) and halving latency with Elasticsearch.”

“Software engineer with hands-on experience spanning backend APIs, streaming data systems, and cloud/infrastructure automation, who is already using agentic AI workflows in a disciplined way. Stands out for combining practical systems work in Spring Boot, Kafka/Spark/ClickHouse, and Terraform/Kubernetes with a thoughtful approach to AI oversight, architecture, and multi-agent orchestration.”

“Full-stack engineer with deep startup experience building products from scratch under ambiguous requirements. Delivered a scalable, admin-configurable notification platform (Spring Boot/Java/Kafka) supporting 50+ notification types across 3 channels for 10k+ users, cutting new notification setup to ~5 minutes. Also built a Tinder-meets-LinkedIn job-swiping app (React/TS + Node/Prisma) and has hands-on AWS production ops (ECS/EKS, RDS, CloudWatch) plus multiple third-party integrations (Stripe, QuickBooks, Twilio).”

“Frontend tech lead for a university e-signature platform (Next.js/React/TypeScript) replacing paper-based signing. Built a trustworthy multi-signer PDF signing workflow with backend-as-source-of-truth state handling, strong quality gates (typed contracts, linting, pre-commit, PR reviews), and performance work like Web Workers for heavy PDF operations.”

“Full-stack engineer with strong production experience improving performance and reliability of data-heavy analytics products. Has shipped end-to-end features spanning Node/Express + PostgreSQL + Redis and React/TypeScript, deployed via Docker/GitHub Actions to AWS EKS with Helm, and monitored with Datadog/CloudWatch; also built a Python compliance automation backend for AWS security monitoring with RBAC, versioned REST APIs, and resilient throttling-aware processing.”

“Analytics professional with experience spanning infrastructure, energy, and digital engagement data. They have built SQL and Python workflows to turn messy operational data into trusted reporting assets, and led a wind turbine SCADA analysis that quantified roughly $1M in cumulative performance loss and translated findings into actionable Power BI dashboards.”

David Momoh

Screened

Senior Full-Stack Engineer specializing in web, mobile, and cloud platforms

Lagos, Nigeria6y exp

“Frontend engineer/lead who has shipped multiple production applications including VentureRamp (multi-platform crowdfunding app, deployed early 2024), DataPotter (large-scale stakeholder tracking dashboard), and Nasdmobile (OTC stock trading app). Emphasizes scalable microfrontend/modular architecture, strong state management (React + TypeScript + Redux Toolkit), and disciplined release practices (feature flags, phased rollouts, monitoring) while leading teams through sprints and knowledge-sharing.”

Thota Rajkumar

Screened

Junior Cloud & AI Infrastructure Engineer specializing in Agentic AI and AWS

San Jose, CA2y exp

“Built and deployed a production AI career-advice agent designed to combat unreliable/generic LLM guidance by grounding outputs in retrieval-first RAG over resumes/job/hiring data, with multi-step reasoning, structured memory, and evidence-only prompting to reduce hallucinations. Implemented the system with LangChain/Python and deployed on AWS as scalable microservices orchestrated via REST and asynchronous calls, iterating closely with career coaches and students.”

DIANA ROMERO

Screened

Director-level business development and sales leader in hospitality, marketing, and events

Albany, CA14y exp

“Sales professional with experience selling streaming, white-label software, and broader SaaS solutions into media, communications, and marketing/revenue-facing teams. Stands out for building pipeline in early-stage environments, leveraging industry relationships and budget-cycle timing to win deals, including a $120K contract and a $30K deal later expanded by $15K.”

“AI/ML engineer with 9+ years of experience building production recommendation and LLM systems end-to-end, from experimentation through deployment, monitoring, and retraining. Stands out for combining strong MLOps discipline with practical GenAI/RAG implementation, including measurable impact such as ~25% higher engagement on an e-commerce recommender and nearly 30% faster knowledge retrieval from internal documents.”