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Vetted React Professionals
Pre-screened and vetted.
Aniruddha Chakravarty
Junior Software Engineer specializing in cloud infrastructure, observability, and full-stack systems
“Built and productionized a predictive maintenance system (predictEngineLife) estimating Remaining Useful Life for PW4000 turbofan engines from large-scale, noisy telemetry—emphasizing modular pipeline design, deterministic preprocessing, and strong observability/guardrails. Also has hands-on experience diagnosing multi-agent LLM customer-support workflows (schema/state issues, fallback paths, regression tests) and has led developer workshops (GDG Pune) while partnering with sales teams on technical discovery and POCs.”
Srinandh Reddy
Mid-Level Software Engineer specializing in backend, cloud, and event-driven systems
“Robotics software engineer focused on backend and distributed systems for real-time robot operations, including sensor ingestion, robot state management, and robot-to-cloud communication. Hands-on with ROS/ROS2 integration and real-time navigation debugging, plus production-grade monitoring, CI/CD, and containerized deployments (Docker/Kubernetes) to improve stability and performance.”
Nicholas Kim
Entry-Level Software Engineer specializing in full-stack and backend development
“Full-stack developer who built a workout tracker feature end-to-end on the PERN stack (Postgres/Express/React), including relational schema design, REST APIs, and optimistic UI updates. Also has Next.js App Router experience (dynamic routes, SSG/React Server Components) and a strong quality mindset from Boston Scientific, where they used TDD to support clinically sound ECG analysis software and drove backend test coverage to 97%.”
Sai Leela Kuragayala
Mid-level Full-Stack Software Engineer specializing in scalable web apps and automation
“UE5 UI engineer who has shipped production-ready HUD/menu frameworks using C++/Slate/UMG and CommonUI, emphasizing MVVM-style architecture for maintainability and designer-friendly iteration. Strong in UI profiling/optimization (Unreal Insights + Slate Profiler), including Slate list virtualization and event-driven updates that improved UI frame time by ~30% in heavy menu scenarios.”
Sai Erramada
Mid-level Full-Stack Java Developer specializing in microservices and cloud-native systems
“Backend engineer with hands-on experience building real-time, event-driven systems at Walgreens, including a Kafka-based prescription status notification service and scalable pipelines for messy prescription/inventory data. Strong focus on reliability patterns (retries, idempotency, DLQs) and iterating based on pharmacist feedback to improve usability.”
Sandipkumar Prajapati
Mid-Level Software Engineer specializing in full-stack systems and authentication
“Full-stack engineer who led production modernization of a legacy, latency-sensitive application into a React + microservices platform, with heavy TypeScript backend work to improve reliability and maintainability. Has operated and scaled authentication/identity services in production, addressing peak-traffic latency spikes via database tuning and improved observability, and emphasizes idempotent, retry-safe workflow design.”
Rahul Ganesan
Intern AI Engineer specializing in LLM systems, RAG, and cloud data pipelines
“Built and deployed a production Dockerized multimodal (voice+text) LLM agent for knowledge management that retrieves from Notion and documents and falls back to Tavily-powered web search with citations when internal notes are missing. Emphasizes production reliability via model-switching fallbacks, caching, strict structured outputs (Pydantic/JSON schema), and MCP-based orchestration with state-aware gating and monitoring to reduce redundant tool calls and improve success rates.”
Sukesh Sadhu
Mid-Level Software Engineer specializing in FinTech payments and event-driven microservices
“Backend/data engineer focused on fintech payments and fraud systems, owning real-time Kafka-based reconciliation pipelines end-to-end (~13k tx/day). Built audit-friendly validation/reconciliation (SQL + Python), kept lag to seconds, and cut errors ~20%, while also shipping Spring Boot APIs with Redis caching and strong idempotency/versioning. Has early-stage startup experience standing up payment services on AWS with Docker + GitHub Actions and production monitoring/incident handling.”
Abhishek Basu
Junior Backend Software Engineer specializing in cloud and AI systems
“Built and shipped LLM-enabled decision systems focused on real production reliability rather than chatbot demos, including a multimodal radiology retrieval platform with 28% relevance gains and 35% lower latency. Also architected a 4-agent employee analytics workflow with structured outputs, traceable orchestration, and strong safeguards for messy real-world data.”
Scott Knight
Director-level software engineering leader specializing in SaaS and Healthcare IT
“Candidate is exploring startup ideas focused on SaaS tools for small and medium-sized businesses, especially IT and HR automation. They have prior experience in VC-backed companies and with accelerators, and stand out for emphasizing real customer feedback and prototyping over echo-chamber startup advice.”
Kuldip Savaliya
Mid Software Engineer specializing in AI automation and full-stack systems
“Built and shipped a production LLM-powered email automation agent for procurement that ingests emails/attachments, classifies requests via rules+embeddings+LLM fallback, enriches responses with SAP inventory data, and generates templated replies. Architected it as an event-driven, idempotent Azure Functions/Queues pipeline with schema-constrained outputs, confidence gating, retries/circuit breakers, and Application Insights monitoring—cutting turnaround time from 4–7 days to near real-time while maintaining zero downtime.”
Antoine Andre
Senior Account Executive specializing in AI/SaaS and technical B2B sales
“Founding recruiter/seller at Remax who built the entire outbound engine from zero—cadences, CRM workflows, automations, Chrome extensions, discovery framework, and ROI templates—without SDRs, inbound, or an existing playbook. Combines consultative selling with technical process-building, and turned a cold-sourced broker into a 5-person team producing $14M in annual volume while reducing meeting conversion timelines by 40%.”
Kush Shah
Junior Full-Stack Software Engineer specializing in web apps and automation
“Backend engineer with hands-on experience building an AI-powered document processing pipeline for insurance workflows from design through deployment and production support. They combine LLM-based extraction with rule-based validation, retries, and observability, showing a pragmatic approach to making AI systems reliable in high-stakes environments.”
Anvith Reddy T
Mid-level AI/ML Engineer specializing in Generative AI and MLOps
“ML/AI engineer with hands-on ownership of fraud detection and investigator-assist systems, combining anomaly detection with RAG-based LLM summarization in production. Stands out for translating research ideas into reliable cloud-deployed workflows that improved precision to 92%, cut review time by 25-30%, and increased investigator throughput by roughly 30% while also building reusable Python infrastructure for team-wide velocity.”
Amarnath Kaushik
Junior Software Engineer specializing in full-stack systems and AI applications
“Full-stack AI engineer who has owned production deployments for both a voice journaling/emotional insights app and a RAG-based research assistant. Stands out for turning messy, failure-prone LLM and document pipelines into reliable user-facing systems through strong debugging, staged workflow design, and post-launch stabilization.”
Pranathi Nallala
Mid-level AI Engineer specializing in distributed systems and LLM applications
“Built production AI agents that convert natural-language requests into structured workflows using LangChain, tool calling, and a Kafka/Kubernetes backend, with strong emphasis on tracing, validation, and self-correcting failure handling. Also drove a zero-to-one Research Day judging platform spanning React, Flask, RAG, and ILP-based assignment optimization for ~100 live posters, achieving 99% uptime and winning Best Web App.”
Rohan Chodapunedi
Entry-level Data Scientist specializing in LLMs and analytics
“Built a zero-to-one AI contract/policy QA agent for compliance and data teams, with a strong emphasis on trust, traceability, and clause-level citations rather than just fluent answers. They combine full-stack product ownership with practical LLM systems design, including hybrid retrieval, structured outputs, and evaluation pipelines to improve reliability, latency, and cost.”
Rohan Karle Sudarshan
Mid-level Software Engineer specializing in AI, backend systems, and data platforms
“Built and shipped production AI features for Aiden, including a natural-language agent and a Knowledge Hub ingestion/retrieval system. Stands out for hands-on debugging of real LLM production issues across providers like OpenAI and AWS Bedrock, improving reliability and achieving 90% response/retrieval consistency through direct LiteLLM integration, validation, monitoring, and async system design.”
Deepak Singh
Mid Software Engineer specializing in systems, CI/CD, and applied machine learning
“Engineer at Syniti who uses AI tools pragmatically to speed development while maintaining quality through rigorous validation, code reviews, and CI/CD. Most notably, they leveraged AI-assisted testing to increase test coverage from 10% to 70%, and they are actively exploring more advanced agent-based development workflows.”
Humera Naaz
Mid-level Full-Stack Developer specializing in cloud-native enterprise applications
“Engineer with hands-on experience embedding AI into software delivery workflows, including Claude-powered PR review, testing, debugging, and multi-agent coding pipelines. They pair AI automation with strong systems thinking around microservices, fault tolerance, multi-AZ design, caching, and security controls like WAF and rate limiting, and also experiment independently with RAG and multi-agent search projects.”
Sakshi Patel
Mid-level Software Engineer specializing in e-commerce and supply chain platforms
“AI-focused developer who has built several practical AI products, including EchoMate, a voice-agent system designed to act as a proxy for doctors and support patients when physicians are unavailable. Also has experience with multi-agent/API-based workflows in a solar suitability project, showing interest in applying AI across both healthcare and climate-related use cases.”
George Platon
Principal Full-Stack Engineer specializing in AI, DevOps, and cloud platforms
“Built a production end-to-end AI video-to-reels clip extraction system using a multi-agent architecture with transcription, captioning, effects generation, and centralized orchestration. Demonstrates unusually strong systems thinking around reliability, observability, evaluation, and production tradeoffs for LLM-powered workflows, including Kubernetes/Kafka-based deployment and regression-driven prompt governance.”
Shady Alzayat
Executive engineering leader and full-stack builder specializing in platforms, payments, and healthcare
“Serial entrepreneur building appetier.com, an agentic restaurant marketing and ecommerce automation platform for restaurants. Previously raised for Atlas Mental Health and brings thoughtful fundraising perspective centered on investor alignment, GTM partnership, and vertical SaaS/SMB infrastructure expertise.”
Atharva Rajesh Patil
Junior Software Engineer specializing in backend systems and cloud-native applications
“Engineer with hands-on experience owning customer deployments for ordering and billing systems at Amdocs, including performance tuning, CI/CD improvements, and post-launch stabilization that delivered about 50% faster execution time. Also built and debugged an LLM-powered task prioritization app using Gemini, Streamlit, Python, and MongoDB, with a strong focus on prompt reliability, validation, and handling inconsistent real-world inputs.”