Vetted JavaScript Professionals

Shram Kadia

Screened

Mid-level Software Engineer specializing in backend systems, cloud-native apps, and AI platforms

Santa Clara, CA4y exp

“Backend/full-stack engineer who has owned production systems end-to-end, including a Dockerized Node.js/TypeScript probabilistic fault-tree analysis service for nuclear safety research deployed on AWS. Also built and operated a FastAPI-based RAG pipeline over 200+ PDFs using FAISS, focusing on low-latency, idempotent workflows and strong observability; experienced with API design and Playwright E2E automation across React/Angular projects.”

Cuichan Wu

Screened

Junior Full-Stack Software Engineer specializing in scalable, AI-powered web apps

Bettendorf, IA1y exp

“Frontend-leaning engineer with production React experience and hands-on Next.js App Router patterns (Server/Client Components, Route Handlers, caching/revalidate decisions). Has built internal sales dashboards and optimized both React UI performance and SQL Server-backed analytics queries, and previously created an onboarding framework at Adobe that evolved into a configurable, multi-team reusable platform in a lean environment.”

Mathew Martin

Screened

Mid-level Software Engineer specializing in cloud data platforms and LLM applications

New York, USA4y exp

“LLM/agent builder with experience shipping production LLM features at an early-stage ed-tech mental wellness startup (conversation analysis + structured feedback via FastAPI, OpenAI API, Render, CI/CD). Also built a multi-step dining concierge agent using OpenSearch over Yelp data with fallback query relaxation, and has enterprise data engineering experience at Capgemini migrating databases to Snowflake with robust ETL normalization and data-quality handling.”

Vincent Chou

Screened

Mid-Level Software Developer specializing in Android frameworks and performance

4y exp

“System-level Android/Java engineer (Motorola) who owned and shipped production reliability fixes in critical services, including resolving a race condition in Android UserManagerService that allowed concurrent duplicate clone-profile creation. Strong focus on correctness, invariants, concurrency safety, and observability; ramping toward product/full-stack work (Next.js/React/Postgres) with solid architectural grounding.”

“Built and shipped an LLM-powered support assistant for a fintech payment reconciliation system that automated failed-transaction analysis at scale. Delivered measurable production outcomes (40% less manual reconciliation, 25% better detection accuracy, 99%+ uptime) and implemented strong reliability patterns (Prometheus/Grafana monitoring, retries/fallbacks, idempotency, Resilience4j circuit breakers) plus iterative retraining driven by real error analysis.”

Kishore Koduri

Screened

Director-level Enterprise Architecture leader specializing in AI and platform transformation

Akron, OH29y exp

“Entrepreneurial candidate with deep technology expertise who has already acted as a founder/principal across a real estate venture and early-stage tech startups. Most notably, they raised approximately $1-2M for a real estate project and describe hands-on ownership from ideation and business case development through ROI validation and investor commitment.”

“Full-stack web developer with experience owning products from client discovery through launch and post-launch iteration, including a complete freelance build for an interior design firm and a large-scale React/TypeScript migration during an internship at Gateway Ticketing Systems. Stands out for balancing strong visual design with performance and SEO, and for improving emergency-use UX in an MVP product through flow simplification and A/B testing.”

“Unity/C# game developer with hands-on experience shipping lightweight, analytics-driven gameplay systems across WebGL, multiplayer, VR, and mobile. Particularly notable for building a cloud-backed character builder with asset-bundle streaming and cross-device persistence, and for creating reusable level design tooling that improved design speed by 2.5x.”

“Backend engineer with strong payments and high-stakes transaction experience, including owning an Apple Pay/Google Pay integration via Stripe end-to-end in production for 100,000+ users. Particularly compelling for teams that need someone who can balance speed, security, and reliability in checkout or other sensitive backend workflows, and who has hands-on incident ownership in production.”

Vamsi Reddy

Screened

Mid-level AI/ML Engineer specializing in healthcare and financial ML systems

Nashville, TN5y exp

“ML/AI engineer with hands-on experience shipping both predictive healthcare models and clinical GenAI assistants into production. They combine strong MLOps depth across Azure and AWS with healthcare-specific safety thinking, including PHI guardrails, retrieval grounding, and production monitoring, and they also built internal Python tooling for fraud ML workflows at Capital One.”

“Backend/ML engineer who built and operated a production WhatsApp assistant end-to-end using a modern RAG stack, delivering >90% automation with sub-2-second latency. Shows strong depth in retrieval quality, observability, evaluation, and incident handling, and has also applied similar AI workflow patterns to a clinical diagnostic assistant processing medical PDFs.”

“Currently at Berryble AI, this candidate is building an LLM-based real-time interview analysis engine using FastAPI, WebSockets, fine-tuned models, and GCP/Cloud Run. They stand out for using AI and agent workflows pragmatically to accelerate development while keeping human ownership over architecture, security, reliability, and maintainability, and they are also pursuing a master's in applied machine learning.”

Akhil Nakka

Screened

Mid-level Software Developer specializing in FinTech and cloud-native microservices

Remote, USA4y exp

“Full Stack Engineer in fintech (JPMorgan) who owns products end-to-end across React UIs and Spring Boot/Kafka backends, with a strong track record of shipping quickly while maintaining reliability via testing, monitoring, and feature flags. Has hands-on experience scaling microservices for high-volume transactions and debugging production latency using ELK/CloudWatch, plus built an internal Python/Flask automation tool adopted by backend engineers to speed API validation and debugging.”

“AI/ML engineer with production experience across both classical ML and Generative AI, including a real-time banking fraud detection platform at Deloitte and a RAG-based cybersecurity threat analysis feature at Accenture. Stands out for owning systems end-to-end—from feature pipelines and model tuning through deployment, monitoring, retraining, and API/platform reliability—with measurable impact on fraud accuracy, false positives, and SOC analyst efficiency.”

“Built production-scale dashboards and real-time data systems across fintech and autonomous driving, with hands-on ownership from React frontend architecture through Python/Kafka/Elasticsearch backend pipelines. At Zoox, led development of an automated safety signal attribution platform that replaced manual engineering calculations and surfaced trends through dashboards.”

“Entrepreneur building a bootstrapped AI-native manufacturing company that combines agentic AI, LLM-assisted CAD/CAM, and in-house CNC machining to speed up hardware iteration. Comes from an early-stage enterprise SaaS background and evaluates opportunities like an angel investor, with strong fluency in VC dynamics and founder-market-team fit.”

“Built and shipped a production LLM feature that converts natural-language search requests into Lucene queries for OpenSearch-backed device event data, improving usability for non-technical users. Brings hands-on experience across the full stack of agentic systems: model training, FastAPI/React integration, Kubernetes deployment on AWS, event-driven orchestration with NATS/Kafka, and production-grade evaluation/observability.”

“AI engineer and current tech lead building a RAG-based multi-agent QA platform for financial document analysis at significant scale (40,000-50,000 documents). They combine Python, CrewAI, FastAPI, Hugging Face embeddings, Pinecone, and AWS SageMaker to deliver retrieval, calculation, summarization, forecasting, and visualization workflows, while leading a small cross-functional team.”

“Full-stack engineer who has owned an AI-powered HTTP monitoring dashboard end to end, from Node.js/MongoDB backend and dashboard UI through deployment and reliability controls. Particularly strong in turning raw technical signals into usable AI-assisted product experiences, with concrete impact including ~60% faster anomaly detection and meaningful AI cost optimization.”

“Candidate has built multiple zero-to-one AI/full-stack products spanning bioinformatics search, rental marketplace semantic search, and an SDR agent for a hospitality startup. Particularly strong at turning LLM/embedding concepts into usable products with modular workflows, explainable outputs, and production-minded infrastructure.”

“Frontend engineer with Oracle Cerner experience building healthcare operations UIs where accuracy, compliance, and workflow efficiency matter. They’ve owned a sophisticated React-based patient record validation and merge interface and also show solid performance instincts through render optimization, state management, and TypeScript-based API modeling.”

“Founder-owner of BoostChat who built a production AI ticket-routing platform for service businesses, bridging Telegram customer chats to contractor workflows in Revolt with measurable gains in speed and satisfaction. Also stepped from QA analyst into a lead software engineer role at Con Edison, helping modernize a legacy mapping platform.”

“AI/full-stack engineer with hands-on experience shipping LLM-powered operational workflows in claims and Medicaid contexts. They built end-to-end TypeScript/React/Node systems with RAG, structured outputs, evals, and human-in-the-loop controls, and can point to concrete impact including 45% lower triage time, 38% better retrieval accuracy, and major manual-effort reductions.”

“AI product leader working at TAU Ventures Innovation Lab and previously at Verint and NYSHEX, with a track record of turning legacy and ambiguous AI opportunities into shippable, human-centered products. Notably led Verint’s evolution into a low-code AI orchestration platform with 20+ capabilities and measurable gains in CSAT, handle time, and recurring revenue, while consistently emphasizing trust, workflow fit, and human-in-the-loop design.”