Vetted Asynchronous Processing Professionals

“Software/product engineer who owns customer-facing internal platforms end-to-end, with deep experience building data pipeline health and data quality tooling (near-real-time alerting and ops dashboards). Strong in React/TypeScript + Python REST architectures and microservices with RabbitMQ, emphasizing reliability patterns (idempotency, DLQs, correlation IDs) and fast, safe iteration via feature flags, testing, and observability.”

sampath achalla

Screened

Mid-Level Software Engineer specializing in backend and full-stack web applications

USA4y exp

“Backend engineer focused on scalable, secure, observable systems—built an async workflow backend with REST APIs and state persistence that improved reliability under concurrent load and cut end-to-end processing time ~40%. Strong in production security for multi-tenant systems (OAuth2/JWT, RBAC, DB row-level security) and in low-risk migrations using feature flags and canary releases, including catching and preventing cross-tenant data access issues with CI-based RLS tests.”

Avanishika Revelli

Screened

Junior Software Engineer specializing in backend, cloud, and robotics automation

2y exp

“Graduate Research Assistant in Robotics at Arizona State University who built an end-to-end LLM-driven task execution framework enabling collaborative robots to convert high-level natural language instructions into safe, executable ROS actions. Implemented robust monitoring, failure detection, and automatic replanning, and addressed real-world issues like timestamp/frame-transform mismatches and heterogeneous robot interoperability using adapter nodes.”

I Anuj

Screened

Junior Backend/Infrastructure Engineer specializing in AWS distributed systems

Chennai, India2y exp

“Backend engineer with 1.7 years of experience plus prior founding experience who has already owned production systems end-to-end in an early-stage environment. Most notably, they rebuilt a failing ingestion pipeline into a stable SQS/Fargate architecture that improved success from 40% to 100%, boosted throughput 10x, and cut processing time by ~75%, while also shipping an LLM-powered fashion search workflow using Vertex AI and Elasticsearch.”

“Backend-focused engineer with 7+ years of experience building cloud-native, distributed SaaS systems in startup-like environments, including healthcare and enterprise automation platforms. Strong in Go/Python microservices, event-driven architectures, and production AI/LLM integration, with hands-on experience scaling Kubernetes-based systems on AWS while balancing speed, reliability, and evolving product requirements.”

Hannah Aron

Screened

Senior Full-Stack Engineer specializing in Python web and cloud applications

Hayward, CA8y exp

“Full-stack engineer with strong Python/React experience who has built systems from scratch, including a custom POS platform as the sole initial engineer. They also bring applied experience across IoT reward platforms, HR matching/search systems, and LLM-powered automation products, with a track record of improving reliability and speed through thoughtful architecture decisions.”

Sakshi .

Screened

Senior Backend Engineer specializing in cloud-native microservices and AI backend systems

Remote, India4y exp

“Backend-leaning full-stack engineer who has repeatedly built web products end-to-end, including an artist booking and event management platform with complex location-based pricing, search, and booking flows. Strongest signal is ownership of backend architecture, API design, database modeling, performance optimization, and production stabilization while also partnering on frontend integration and UX improvements.”

Sampath Achalla

Screened

Mid-level Full-Stack Engineer specializing in Golang and cloud-native FinTech systems

USA3y exp

“Backend-leaning full-stack engineer in fintech/payments who shipped an end-to-end Stripe payments + webhook system for a financial microservices platform, emphasizing ledger accuracy via idempotency, transactional writes, retries, and DLQs. Also delivered a real-time React/TypeScript payment status dashboard informed by user interviews, and improved production performance by 35% p95 latency through PostgreSQL tuning and Redis caching on AWS.”

“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.”

Ajay Kudapa

Screened

Mid-level Software Engineer specializing in Healthcare IT and Web3

4y exp

“Software engineer with experience spanning healthcare middleware (patient records + insurance integration) and an AI fantasy football product built with React/TypeScript, Firebase, API gateways, and pandas-based data pipelines. Has hands-on microservices scaling experience (latency mitigation, async migration, state-based redesign) and built an internal feature-toggle dashboard that improved demo efficiency and sales outcomes.”

Nicolas Cols

Screened

Mid-level Unity Game Developer specializing in multiplayer and performance optimization

Córdoba, Argentina6y exp

“Senior gameplay/multiplayer engineer based in Argentina with hands-on experience building Unity/C# networked systems end to end, including Mirror-based gameplay architecture and server-authoritative MMO-style networking. Particularly strong in multiplayer stability, sync/prediction design, and performance profiling across VR and mobile, with thoughtful early-stage architecture ideas for AI/LLM-enabled game features and internal pipelines.”

“Built AI-powered products across both healthcare and financial services, including a privacy-conscious assistant for elderly health check-ins and a production RAG system for high-stakes financial document analysis. Stands out for combining full-stack engineering with strong LLM reliability practices—grounding, structured outputs, fallback handling, monitoring, and human-in-the-loop controls—while delivering measurable impact on accuracy, speed, and system performance.”

“Product-minded full-stack engineer with hospitality tech experience who owned and scaled a multi-region guest verification/check-in workflow (ID/passport scanning, OCR, and government submissions) and built internal tools that cut manual entry up to 80%. Also built a React/TypeScript + FastAPI RAG “second brain” with async ingestion workers and an event-driven e-folio email microservice hardened with idempotency and retries.”

Swapnil Sanjay Pawar

Screened

Junior Full-Stack Software Engineer specializing in GenAI and web platforms

Atlanta, GA2y exp

“AI/software engineer with hands-on experience deploying an LLM-powered quiz generation platform for students, integrating Python services with Gemini APIs plus frontend and database components. Emphasizes production-grade reliability through observability, schema validation, async processing, and performance tuning under high concurrency, and has collaborated with product/operators (e.g., at Colombo AI) to translate real-world constraints into scalable technical solutions.”

Charmi Dharmendrakumar Parmar

Screened

Mid-Level Software Engineer specializing in full-stack and cloud-native systems

Alpharetta, GA4y exp

“Backend/full-stack engineer who owned a cloud-native, AWS-based microservices backend for an HRIS product used by ~10,000 users, including onboarding and workflow orchestration. Strong production focus on event-driven architecture, idempotency/retries, observability, and developer-friendly API design (OpenAPI, versioning, JWT), plus hands-on Selenium automation for resilient checkout-style flows.”

“Salesforce-focused engineer with hands-on ownership of complex Sales Cloud and Service Cloud solutions, including automated lead-to-opportunity lifecycle workflows, LWC-based lead management UIs, and Aura case management consoles. Stands out for making thoughtful architecture tradeoffs between Flow and Apex, with strong attention to scalability, governor limits, UX performance, and post-release monitoring.”

“Senior full-stack engineer with 7+ years of Python-centric experience who has worked in lean startup environments and personally drove backend architecture for a data-intensive B2B analytics platform. Stands out for navigating ambiguous, fast-changing requirements while improving scalability and performance through Redis, Celery, RabbitMQ, and PostgreSQL optimization.”

“Built an AI GTM Copilot that consolidated 5+ sales tools into a single browser-based workflow for sales teams, combining LLMs, data enrichment, and outreach automation. Brings a rare blend of ML, backend, and front-end experience, with concrete wins in performance optimization, workflow design, and measurable UX improvements.”

“Frontend-focused product builder who designed and implemented an internal PCB quoting and pricing platform at SVTronics end to end. They translated a vague operational problem into a shipped React/TypeScript workflow that cut quote preparation time by about 40% and reduced manual errors, showing strength in both UX simplification and production delivery.”

“Full-stack engineer with experience building a NASA-funded simulation management platform using React, TypeScript, Next.js, PostgreSQL, AWS, and Docker. Stands out for owning complex, long-running workflow features end to end in production and driving measurable performance improvements, including a 40% database load reduction and API latency improvements from roughly 500ms to under 200ms through Redis caching and async architecture.”

“Full-stack engineer who built an enterprise knowledge assistant from scratch using React, FastAPI, PostgreSQL, ChromaDB, and OpenAI, with role-scoped cited answers over internal PDFs. Stands out for combining hands-on LLM/RAG architecture with rigorous evals, improving grounded QA accuracy from 85% to 95% and deploying a production-style multi-tenant system on AWS.”

“Built a production-grade clinical and insurance document AI system in a HIPAA/PHI-regulated environment, taking it from experimentation through Azure deployment, monitoring, and iterative improvement. Stands out for translating RAG/LLM research into reliable microservices with strong safety controls, drift monitoring, and human-in-the-loop workflows that cut manual review time by 60-70%.”