Vetted Integration Testing Professionals

“Software engineer with experience across edtech, live gaming, and an AI document intelligence platform, delivering end-to-end customer-facing features and production backends. Built secure, automated live-session scheduling integrating Zoom and TalentLMS (JWT/RBAC, idempotency, transactions) cutting setup time from ~3 minutes to under 1 minute, and optimized real-time gaming dashboards/APIs with query tuning, caching, and CDN improvements (~60% latency reduction under peak load) on AWS.”

“Built a production anomaly-detection workflow at VDOIT for messy cloud billing/cost data, emphasizing validation, idempotency, retries, and monitoring. Delivered measurable impact by preventing ~$50K/month in overspend and improving response time, and is now applying the same multi-step pipeline approach to LLM-based agent workflows.”

“Backend/data engineer who has owned end-to-end production pipelines and data services, processing ~500K–1M records/day from APIs/logs into MySQL and serving via REST APIs. Strong focus on reliability and data quality (ELK + structured logging/monitoring), with measurable improvements (~30% reduction in bad data, ~20% query performance gains) and experience operating external data collection/scraping systems with anti-bot and schema-change resilience.”

Pranav Mishra

Screened

Junior Machine Learning Engineer specializing in LLM agents, RAG, and MLOps

Charlotte, NC2y exp

“AI/ML engineer who has shipped production systems across computer vision and conversational agents: built a YOLOv8-based wheel fitment pipeline at a Techstars-backed automotive startup, focusing on sub-second latency, monitoring, and robust fallback mechanisms that drove 2–3x page view growth and +5–6k users. Also built a voice-based interview platform orchestrating Deepgram + GPT-4 Mini + OpenAI TTS with FSM-driven reliability, and has hands-on RAG experience (LangChain, hybrid retrieval, cross-encoder reranking, custom pseudo-query generation).”

Ram Abhinav Vedant Madabushi

Screened

Junior Full-Stack/AI Engineer specializing in web platforms and LLM applications

Palo Alto, CA2y exp

“Backend engineer from FoodSupply.ai who built and evolved a scalable restaurant/supplier product and order management platform using Node.js and REST APIs. Implemented a hybrid MySQL+MongoDB data architecture, optimized performance with Redis/Prisma, and led a phased migration with feature flags and a temporary sync layer to maintain data consistency. Strong focus on production security (OAuth2, RBAC, row-level security, AWS IAM) and reliability practices (testing with Pytest, Docker/AWS pipelines).”

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.”

Victoria Magaziner

Screened

Senior QA Automation Engineer specializing in end-to-end test automation for FinTech and automotive platforms

Los Angeles, CA9y exp

“QA Engineer with 8 years owning end-to-end quality on high-traffic, live fintech and automotive platforms (Fuse Autotech), specializing in critical financial and e-signing workflows. Combines API testing (Postman), log observability (Kibana/Logz.io), and disciplined Jira/Xray processes to accelerate triage and shorten release cycles (1 week to 3 days) while reducing production issues and integration/regression defects with measurable impact.”

Sampath achalla

Screened

Mid-level Systems Software Engineer specializing in distributed cloud infrastructure

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.”

Shayan Naqvi

Screened

Mid-level Full-Stack Engineer specializing in AI and geospatial SaaS

Lahore, Pakistan3y exp

“Full-stack engineer in the renewable energy software space who has built an LLM-powered due diligence reader and self-serve geospatial upload workflows that materially reduced customer turnaround time. Combines Angular/NestJS product engineering with AI pipelines, geospatial data handling, and strong user-feedback-driven iteration, plus a side-project builder streak with a Spotify analytics app.”

Tejal Patel

Screened

Intern Software Engineer specializing in full-stack and backend systems

New York, USA5y exp

“Full-stack developer intern who significantly owned parts of a recruitment platform used by recruiters, job seekers, and company administrators. They stand out for building and optimizing complex React-based dashboards for large datasets, improving responsiveness through debouncing, memoization, reusable component architecture, and thoughtful UX simplification.”

“Unity developer focused on VR/AR multiplayer, with hands-on experience building Photon Fusion/PUN systems including networking, sync, and matchmaking. Has scaled a modular multiplayer architecture to handle more players/features while addressing latency and data consistency, and has optimized Meta Quest/mobile performance using pooling, LODs, batching, and profiling.”

“Frontend engineer at LodestonePM who led end-to-end delivery of an AI release-notes generator (OpenAI API) and a Kanban-style release board in Remix/React/TypeScript. Demonstrated scalable architecture (bridging tables, upserts), strong QA practices, and measurable performance wins (200+ item loads reduced from 10–20s to a few seconds via caching/pagination), plus UX improvements like simplifying a Jira integration flow.”

“Built and deployed a production AI accessibility platform that turns chart and image-based graphs into real-time audio narratives for visually impaired users. Implemented a ResNet-based CV + OCR + NLP + TTS pipeline and improved performance through preprocessing, Redis caching, and Kubernetes autoscaling/rolling updates on AWS to handle traffic spikes with no downtime.”

“Manual QA tester with experience in black-box/white-box and positive/negative testing, using meeting minutes to translate requirements into executable test scenarios. Comfortable working in a structured workflow using Trello for task tracking and prioritizing urgent issues first; open to learning new standards and workflows.”

“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.”

“Full-stack engineer who shipped and owned a production Document Chat feature built with Next.js App Router/TypeScript and a Node/Express RAG backend, including JWT-secured route handlers and streaming responses. Demonstrated strong post-launch ownership by improving latency (~30%) via MongoDB indexing/query optimization and reducing AI costs through caching, backed by profiling with React Profiler and Chrome DevTools.”

“Full-stack engineer focused on Next.js (App Router) and TypeScript who has shipped and owned production role-based dashboards end-to-end, including post-launch reliability/performance work. Demonstrated measurable UI performance improvements (35–40% faster initial load) and strong backend rigor with Postgres query/index optimization (300ms to 30ms) plus durable Temporal-orchestrated onboarding/data-sync workflows with idempotency and retry strategy.”

“Software engineer (internship experience) who built and owned an AWS serverless multi-user “challenge” feature end-to-end (UI + REST APIs + DynamoDB + deployment), delivering measurable gains in latency (-30%), debugging time (-50%), and join drop-offs (~-30%). Also productionized a multilingual RAG-based QA system with vector retrieval and guardrails, improving accuracy to ~85% and driving ~20% DAU growth.”

Vishnu Priyan Sellam Shanmugavel

Screened

Mid-Level Applied AI Engineer specializing in LLM services, RAG, and OCR/NLP extraction

Arlington, VA4y exp

“Backend/platform engineer who built and evolved a large-scale healthcare document processing system (OCR + LLM orchestration) in Python/FastAPI on Google Cloud (Cloud Run, GCS, Firestore), processing ~1.5M files per batch and tens of millions overall. Emphasizes reliability and operational safety via deterministic IDs, idempotent state machines, strong observability, and self-healing reconciliation, plus disciplined migrations using dual-run validation and incremental rollouts.”

Tanvi Kulkarni

Screened

Intern Full-Stack Engineer specializing in Java, React, and cloud-native backend systems

Santa Clara, CA1y exp

“Frontend-focused engineer with startup experience (SmartPath, OPC AI) who owned and evolved an internal React/TypeScript component library treated like OSS—refactoring core form and API wrapper modules for stability, type safety, and smaller bundles. Comfortable diagnosing production issues via logs/API traces and shipping end-to-end fixes with tests and documentation, including internal workshops to drive adoption.”

“Built and shipped Site Audit AI, a production multi-turn Claude-based agent that autonomously crawls websites, calls tools, and generates scored audit reports—reducing a manual 2-3 hour developer workflow to under 60 seconds. Also brings practical experience integrating inconsistent payroll/HR data across platforms like QuickBooks and Keka, with a strong focus on validation, fault tolerance, and resumable workflows.”

“Built and owned a production RAG-based internal knowledge assistant end-to-end, from experimentation through cloud deployment and monitoring. Demonstrated strong practical GenAI judgment by choosing prompt optimization and retrieval tuning over fine-tuning for dynamic data, driving a 40% to 50% reduction in time to answer while improving relevance, lowering hallucinations, and increasing productivity.”

“Built an end-to-end agentic population health strategy copilot for healthcare leadership, turning broad chronic disease questions into structured, evidence-backed strategy briefs. Stands out for combining healthcare domain knowledge with production-grade GenAI implementation, including LangGraph orchestration, Databricks/MLflow deployment, human review, and quality gates focused on citations, metrics, risks, and safety.”

“Backend/distributed-systems engineer with 9 years of Go experience, focused on financial-services platforms where performance, reliability, and regulatory auditability are critical. He has built low-latency market data infrastructure (p99 under 8ms) and optimized compliance/reporting systems used by finance and audit teams, combining strong systems design with practical production operations.”