Vetted gRPC Professionals

Shehab mohamed mohamed

Screened

Junior AI Engineer specializing in MLOps, LLMs, and multi-agent systems

Cairo, Egypt2y exp

“ML/AI engineer focused on production-grade systems, with experience building a low-latency multi-agent 'neural concierge' booking platform used across domains like restaurants and hospitals. Also worked on a healthcare computer vision system for nystagmus/eye-movement analysis, showing a mix of scalable LLM infrastructure, MLOps, and safety-conscious medical AI experience.”

sajda kabir

Screened

Junior Software Engineer specializing in AI, voice, and full-stack product engineering

Kolkata, India2y exp

“Product-minded full-stack engineer from SuperU who built AI voice-agent infrastructure end-to-end, from React/TypeScript campaign UIs to a forked n8n orchestration backend and Postgres multi-tenant data model. Stands out for shipping quickly in ambiguous startup environments, debugging deep reliability issues across layers, and delivering measurable gains like activation rising from 20% to 70%+ and call drops falling below 0.5%.”

Iskhak Ishmakhametov

Screened

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

Bellevue, WA7y exp

“Full-stack product engineer with a strong real-time systems focus: built and rolled out a WebSocket-based notifications system (with robust reconnect/resync and event ordering protections) that cut update latency to under 200ms. Also owned a workflow automation platform backend in FastAPI (JWT/RBAC, versioned APIs, standardized errors), designed the PostgreSQL schema for workflows/tasks/executions, and operated deployments on AWS ECS Fargate with blue-green CI/CD and performance stabilization via caching and autoscaling.”

“ML/NLP engineer who has built production systems end-to-end: a real-time recommendation platform (100k+ profiles) using BERTopic-style clustering and a RAG-based news summarization/recommendation stack with ChromaDB. Strong focus on scaling and reliability (GPU batching, Redis caching, Kafka ingestion, Docker/Kubernetes, Prometheus/Grafana) and on maintaining model quality over time via drift monitoring and retraining triggers.”

“Built and shipped production LLM-driven pipelines for clinical data processing, turning semi-structured inputs into validated structured outputs for downstream analytics. Emphasizes predictability and safety via strict JSON schemas, state-machine orchestration, backend-controlled tool calling, and robust fallbacks (rule-based checks/manual review) plus monitoring and offline/online evaluation loops; also has experience hardening workflows against messy ERP/finance data with idempotency and state tracking.”

Sai Vamsee Bandaru

Screened

Entry-level Data Analyst and AI Engineer specializing in machine learning and LLM systems

New York, NY1y exp

“Founding-engineer-oriented full-stack product engineer who built an AI tutor system end-to-end, spanning React UI, FastAPI backend, retrieval/LLM pipelines, and Postgres optimization. Stands out for combining product thinking with deep systems work: improving onboarding and activation, shipping quickly with beta users, and abstracting reusable retrieval infrastructure for multiple use cases.”

Volodymyr Rudenko

Screened

Senior Front-End Engineer specializing in React/TypeScript and Next.js for FinTech & SaaS

Calgary, AB9y exp

“Frontend engineer with deep experience in crypto/fintech products, including leading a Next.js/TypeScript crypto wallet and microfrontend platform at 200–300k daily transactions and building a real-time trading dashboard. Strong in scalable architecture (microfrontends + BFF), quality systems (Storybook, testing, Sentry), and performance optimization (including a 30% bundle-size reduction), with proven feature-flagged rollouts and iterative delivery.”