Vetted Redis Professionals

Dhairya Gajjar

Screened

Mid-Level Software Engineer specializing in Healthcare Data Platforms

Remote2y exp

“Backend/ML engineer with healthcare domain experience building secure Medicare/Medicaid data APIs and real-time patient risk scoring. Shipped an end-to-end ML pipeline (scikit-learn/XGBoost) served via SageMaker and integrated into Flask APIs, with strong production reliability practices (Kafka schema validation, regression replay, observability, drift monitoring, and human-in-the-loop guardrails).”

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.”

Abhay Bisht

Screened

Junior Software Engineer specializing in AI and full-stack SaaS

Bangalore, India2y exp

“AI-first developer who reports using agents for roughly 85% of coding work, with a disciplined process centered on detailed specs, prompt design, review, and testing. Has built a personal multi-agent orchestration setup with specialized agents for testing, PR extraction, review, and synthesis, and stays current through AI engineering newsletters and a network of AI companies.”

“Robotics software engineer focused on reliability in real-time sensor pipelines and ROS/ROS2 integration, with hands-on experience hardening systems against noisy data, dropouts, and network variability. Uses ROS introspection tools plus simulation (Gazebo/Webots) to diagnose latency and stability issues before hardware deployment, and supports repeatable rollouts via Docker and CI/CD.”

“Full-stack engineer (4+ years) with a Master’s in Computer Science who owned end-to-end customer-facing social networking features at NextBits, building TypeScript/React/Next.js + NestJS systems with microservices, RabbitMQ, MongoDB, and Redis. Experienced scaling real-time notifications/messaging/presence to millions of concurrent users with sub-100ms performance targets, zero-downtime CI/CD, and internal tooling for monitoring AI/ML pipelines and queue backlogs.”

Maheswari Thokala

Screened

Mid-level Full-Stack Engineer specializing in cloud microservices and REST APIs

CA, USA4y exp

“Backend engineer building an AI-powered social media platform on AWS, with hands-on experience shipping LLM-backed application features and improving production performance under high traffic. Strong focus on reliability/observability (CloudWatch, structured logs, health checks) and database optimization (MongoDB explain/slow logs, indexing, caching, connection pooling).”

Monil Patel

Screened

Junior Software Engineer specializing in backend and cloud systems

Pennsylvania, USA2y exp

“Full-stack engineer with hands-on experience spanning analytics products and fintech infrastructure. Built a YouTube Data Aggregator end-to-end in 2025 with ingestion, dashboards, and predictive modeling, and also shipped Stripe webhook/payment systems at FinPay supporting $5M+ in transactions with 99.9% uptime.”

Ahmad Rayyan

Screened

Entry-level Full-Stack Engineer specializing in Applied AI and multi-agent systems

Pakistan1y exp

“Built both traditional full-stack products and advanced LLM systems, from a React/Flask dashboard used by instructors to monitor GitHub contribution patterns to multi-agent benchmark infrastructure at Analytiverse. Particularly strong in evaluation-heavy AI engineering: designed executable verifiers, force-zero anti-reward-hacking checks, and token-optimization strategies that delivered a 40-point pass-rate lift and 90x token reduction on SwarnBench tasks.”

“Early-stage product engineer who built an AI persona chat system end to end at Super Intro, spanning Next.js frontend, GraphQL/real-time backend, retrieval memory, and LLM-based matching. They combine strong TypeScript rigor with practical AI systems design, and cite measurable impact including ~40% engagement growth, ~30% recall improvement, and lower LLM costs in production.”

“Python backend developer from Larix Technologies who built and scaled microservice APIs for an omnichannel messaging SaaS (WhatsApp/Instagram/Facebook) and led production performance fixes during peak traffic, cutting webhook latency ~50%. Also shipped applied AI products end-to-end: a RAG-based PDF assistant (LangChain + Mixtral via Groq + React) and a BI agent that plans/executes/verifies multi-step analytics with strong guardrails and auditability.”

John Kenny

Screened

Senior Full-Stack Engineer specializing in Web3 and FinTech

Global, Remote6y exp

“Full-stack engineer with deep startup experience (pre-seed through IPO/SPAC) currently building a Next.js/TypeScript SaaS sports analytics platform with a complex Postgres-based entitlement/ACL system. Has delivered measurable UX/business impact (35% retention lift, 40% volume increase) and built production-grade daily ETL + model training/inference workflows with validation and checkpointing for reliability.”

“Full-stack product engineer who has built both a production-grade React/Next.js analytics platform and a Stripe-based subscription system end to end, with measurable business impact including churn reduction, reporting automation, and cost savings. Also stands out for 0-to-1 work in the digital art space, where they built an AI-powered cataloguing and delivery pipeline over 30TB of assets using computer vision, Shopify, and cloud infrastructure.”

“Engineer with growth-stage startup experience on a 6-7 person cross-functional team, working across backend, data, and frontend systems. They’ve driven concrete improvements to high-volume data ingestion pipelines through batch processing and database optimization, and have built B2B SaaS data platforms for enterprise customers with multi-tenant support, integrations, and scalable backend services in Python and Go.”