Vetted Software Engineers

“ML/NLP engineer with banking domain experience who built a GenAI-powered fraud detection and risk intelligence system at Origin Bank, combining RAG (LangChain + FAISS), fine-tuned BERT NER, and GPT-4/Sentence-BERT embeddings. Delivered measurable impact (25% higher fraud detection accuracy, 40% less manual review) and emphasizes production-grade pipelines on AWS SageMaker/Airflow with strong data validation and scalable PySpark processing.”

“Backend engineer who built an Emergency Alert System with Virginia Tech for the City of Alexandria, focusing on real-time ingestion, secure dashboards, and AI-assisted prioritization. Emphasizes high-stakes reliability with guardrails (hybrid rules+LLM, confidence-based fallbacks), scalable async processing, and defense-in-depth security (JWT/RBAC plus database row-level security).”

“QA automation-focused candidate with hands-on ownership of unit and integration test suites, including CI/CD integration in GitLab. Caught a database-query regression that would have shipped incomplete API data by relying on automated integration tests, and has practical Cypress experience stabilizing flaky tests using cy.intercept()/cy.wait() and stable selectors.”

“Backend/AI engineer who has shipped production LLM systems end-to-end, including an AI request-routing service (FastAPI + BART MNLI + OpenAI/Gemini) that improved accuracy ~25% after launch via eval-driven prompt/category iteration. Also built an enterprise document intelligence/RAG platform on Azure (Blob/SharePoint/Teams ingestion, OCR/NLP chunking, embeddings in Azure Cognitive Search) with PII guardrails (Presidio), confidence gating, and scalable event-driven pipelines handling millions of documents.”

“Backend-focused TypeScript/Node.js engineer who owned a production microservice for transactional workflows in a React + microservices platform, integrating REST and Kafka event processing. Emphasizes operability and correctness (idempotency keys, exponential backoff retries, DLQs, centralized logging/metrics/alerts) plus strong API DX via versioning and Swagger/OpenAPI with improved error contracts based on developer feedback.”

“AI research engineer who has built and tested LLM agents end-to-end, including a Telegram real-time voice-to-typing assistant integrated with calendar scheduling. Emphasizes production concerns (security via mic-triggered activation, multi-model fallbacks, monitoring) and agent predictability using a GPT-3.5-based critic plus structured outputs (Pydantic) and ReAct-style orchestration.”

Raghavendra Dubey

Screened

Mid-level Software Engineer specializing in Java microservices and cloud-native systems

CA, USA5y exp

“Enterprise workflow/product engineer (DXC) who owned a customer-facing workflow application for 500+ users and improved performance ~30% through API/SQL optimization, caching, and CI/CD-backed iteration. Experienced designing React/TypeScript + Java/Spring Boot systems and operating microservices with RabbitMQ/Kafka-style messaging, emphasizing reliability via DLQs, backpressure, and strong observability. Also built an internal automation dashboard adopted by support/ops teams to cut manual work and reduce SLA misses.”

Rasega Babu Kavitha

Screened

Mid-Level Full-Stack Software Engineer specializing in Java/Spring and React

Boston, MA4y exp

“Full-stack engineer who has shipped a real-time social engagement feature (live messaging + personalized feeds) for a career networking platform, owning everything from WebSockets/SSE and JWT+Redis auth through Docker/Kubernetes production deployment. Also built a production Flask backend for an AI-driven movie recommendation system on AWS, with strong API design (versioning/error standards) and hands-on performance tuning (Typesense +47% query improvement, Postgres indexing, Redis caching, CloudWatch-driven incident response).”

“Full-stack product engineer who builds and owns production features across Next.js/React/TypeScript and Java Spring Boot, with strong Postgres data modeling and performance tuning. Has delivered measurable improvements (60%+ faster renders, 2s→100ms queries, 50% lower workflow latency) and built reliable Kafka-based workflows with robust observability (Prometheus/Grafana/Alertmanager) and high test coverage.”

John Kalyango

Screened

Senior Full-Stack Software Engineer specializing in geospatial and mobile data collection

Germany9y exp

“Frontend engineer who led end-to-end development of a React-based carbon credits data collection and analysis tool, focusing on scalable architecture and performance (code splitting, SWR caching, memoization, Lighthouse monitoring). Experienced building complex route-driven TypeScript wizards with Redux/Rematch state persistence, and refactoring legacy monolithic UI into reusable, tested, documented components while shipping deadline-driven features using feature flags and tight QA collaboration.”

Cody Feda

Screened

Principal Full-Stack Engineering Leader specializing in forward-deployed SaaS platforms

San Francisco, CA14y exp

“Hands-on builder and workshop facilitator focused on getting LLM/agentic and dev-tools products from prototype to production. Has delivered iterative production deployments for a construction client (estimating/invoicing on EC2), debugs LLM regressions with monitoring plus prompt optimization, and has facilitated multiple developer workshops while helping founders improve onboarding and time-to-first-success using tools like PostHog.”

Vedant Singh

Screened

Junior Cloud Platform Software Engineer specializing in AWS, Kubernetes, and CI/CD

Concord, CA2y exp

“Cloud/platform engineer with hands-on delivery across Azure and AWS, including standing up a CIS-compliant Azure environment and integrating Azure OpenAI Foundry to automate finance invoicing. Has scaled platform capabilities across large org footprints (dynamic CI/CD pipelines for ~94 teams across 200+ repos) and replaced a $1M/year vulnerability patching vendor by building an internal AWS-based patching and monitoring solution for ~1000 servers.”

Vinícius Samuel

Screened

Senior Unity Game Developer specializing in mobile and VR experiences

Dublin, Ireland8y exp

“Unity developer with experience building an optimized comic-reader/content delivery system for Marvel HQ using Addressables—avoiding bulk downloads and dynamically loading/unloading pages to reduce mobile memory/disk usage and improve runtime performance. Also has multiplayer experience using server-authoritative Netcode with prediction and deterministic battle behavior, including real-time kinematic body tracking, and leverages AI tools (Cursor/Manus) to speed prototyping and refactoring.”

Eric Vuu

Screened

Mid-Level Full-Stack Software Engineer specializing in cloud infrastructure and web applications

Huntington Beach, CA5y exp

“Software engineer turned solutions/technical support engineer with 5+ years of experience supporting and migrating a custom CRM used by U.S. House of Representatives offices. Has hands-on ownership of database export/import scripting, API key-based integrations, and production troubleshooting, and also consults government customers on procurement/CLM workflows while partnering with sales/marketing on demos and adoption use cases.”

Tracy Nguyen

Screened

Mid-Level Software Engineer specializing in Front-End Web Development

Toronto, Canada3y exp

“Frontend engineer with React + TypeScript experience building internal dashboards and a nonprofit festival website delivered end-to-end in 6 weeks. Emphasizes scalable quality practices (documentation ownership, code reviews, CI/CD, testing) and user-centered delivery, including accessibility, multilingual support, and enabling non-technical stakeholders to update content.”

Abhishek Ingle

Screened

Junior Full-Stack & AI Software Engineer specializing in React/Next.js and LLM systems

Bloomington, IN2y exp

“Backend engineer with hands-on experience building low-latency, high-concurrency real-time chat on AWS (Node.js/Socket.IO/MongoDB) and improving reliability under unstable networks, contributing to ~40% user adoption growth. Also built FastAPI-based AI assistant context retrieval (RAG) APIs with embeddings/vector search, and has strong production experience in rate-limit handling, async refactors with safe rollout, and Supabase Auth/RLS optimization.”

adam melhem

Screened

Executive Full-Stack Software Engineer specializing in .NET and Angular

Israel12y exp

“Backend-focused engineer with Python experience building network design/exploration tooling integrated into an existing infrastructure framework via APIs, including use of graph algorithms for routing/target discovery. Has also supported .NET to .NET Core and database migrations by strengthening test infrastructure, and improved messaging-system stability (RabbitMQ) through performance monitoring and memory leak troubleshooting.”

Aditi Deshpande

Screened

Mid-level Software/AI Engineer specializing in GenAI, AWS, and microservices

Remote, United States4y exp

“Built a production AI pipeline at EyCrowd to automatically grade shaky outdoor user-submitted brand videos using CV + CLIP/BLIP and a LangChain RAG layer per brand, with GPT-4 generating structured JSON explanations and grades. Optimized for latency and cost (batch PyTorch inference, caching), cutting review time from ~8 minutes to <2 minutes while reaching ~90% alignment with human graders and supporting thousands of videos/day.”

“Independent product builder with several live startups spanning transit, gaming, and SaaS/API tools. Notably built a Cyprus bus routes app before transit data was broadly available on Google Maps, and is currently maintaining products like CountriesDB and HolidayDB while pursuing SEO-led growth and validating ideas solo before expanding.”

Thanmayi Ravuri

Screened

Entry Software Engineer specializing in cloud backend and microservices

Tempe, AZ1y exp

“Built production-oriented LLM agent systems for incident investigation and CRM workflows using LangGraph, FastAPI, AWS, and retrieval grounding. Stands out for treating agents like real software systems—adding schema enforcement, retries, fallbacks, monitoring, and eval loops—and tying that work to measurable gains in accuracy, latency, and analysis speed.”

Pranav Zagade

Screened

Junior Software Engineer specializing in full-stack and AI systems

Arizona, USA3y exp

“Built and shipped an LLM-powered support agent for Community Dreams Foundation that automated intake and Jira ticket creation using RAG, structured outputs, and strong production guardrails. Demonstrated practical production AI experience with 92% routing accuracy, 98% uptime, and a 31% improvement in first-response accuracy, plus hands-on work in observability, evals, idempotency, and failure handling.”

Kunal Sanghvi

Screened

Mid-level Data Engineer specializing in AI, NLP, and LLM systems

USA3y exp

“Built and deployed a production AI customer support chatbot at Unique Design Inc. using FastAPI, AWS, Docker, and retrieval-based grounding on internal documents. Stands out for hands-on ownership across discovery, deployment, incident debugging, and post-launch iteration, with a strong focus on making LLM systems reliable and safe in real business workflows.”