Vetted WebSockets Professionals

“Full-stack product engineer who has built AI-assisted CRM and agent workflows in Project SARA and operational systems like payroll for a staffing platform. Stands out for combining React/TypeScript, Django/Postgres, real-time systems, and LLM orchestration with strong product instincts—delivering measurable gains in response time, conversion, and engineering leverage.”

Srinivasan Gomadam Ramesh

Screened

Mid-level AI/Data Engineer specializing in agentic AI and data platforms

Redmond, WA7y exp

“AI/LLM engineer who built a production resume-parsing and candidate-matching platform at Quadrant Technologies, combining agentic LangChain workflows, VLM-based document template extraction (~85% accuracy), and a hybrid RAG backend for resume-to-JD search. Notably integrated automated LLM evals and metric-based CI/CD quality gates to catch silent prompt/model regressions, and led a 3-person team across frontend/backend/testing.”

“Built and shipped AI products at Humanitarians AI, including a full-stack multi-agent platform that consolidated six faculty AI tools into one interface and achieved 100+ user adoption, 70% less workflow switching, and a 6x latency improvement. Also designed a grounded document parser using FAISS and structured LLM outputs that reduced hallucinations by 60%, showing strong depth in both product-minded engineering and production AI systems.”

“Full-stack engineer with hands-on ownership of a production AI knowledge assistant used by 10,000+ daily users. Combines React/Next.js frontend work with FastAPI, AWS serverless, and RAG architecture using GPT-4, LangChain, and Pinecone, with measurable impact on relevance, latency, uptime, and support deflection.”

Nandini Patel

Screened

Junior Mobile App Developer specializing in cross-platform sports fan engagement

Los Angeles, CA3y exp

“Front-end engineer with hands-on experience building analytics-heavy React dashboards and performance-sensitive browser UIs across marketing and live-broadcast products. Stands out for combining deep browser fundamentals, analytics-driven UX improvements, and strong TypeScript discipline to ship interfaces that are both measurable and reliable.”

“Backend/full-stack engineer with experience spanning AI-powered fintech features and high-volume roadway surveillance/ALPR platforms. They have owned production APIs, improved API latency by 35% through database/query optimization, and helped drive a Kafka-based ingestion architecture that increased throughput by 30% while improving reliability at scale.”

“Founding-engineer-style full-stack and AI product builder who has shipped production conversational agents in hospitality and earlier helped build an AI sports analytics startup through acquisition. Stands out for combining React/TypeScript frontend ownership, FastAPI backend design, and sophisticated LLM/RAG/agent systems with strong production monitoring and clear business impact.”

“Candidate worked on an AI-powered commercial real estate document analysis product at Ariesview, building workflows that ingest leases and property reports, run OCR, persist structured outputs, and support grounded Q&A via RAG. They stand out for practical ownership of messy production problems like noisy PDFs, document-state consistency, and backward-compatible schema migrations in a fast-moving product environment.”

“Backend Python engineer who has built an LLM agentic tutoring/assignment helper with a custom pipeline for parsing visually complex textbooks (integrating AlibabaResearch VGT and implementing missing preprocessing from the paper), improving RAG grounding with ~90% cleaner extracted text. Also led major platform scaling work by refactoring monolithic image processing into Celery-based async microservices on AWS (GPU/CUDA + S3), and implemented Kafka streaming for payment webhooks with strict ordering, idempotency, and multi-zone fault tolerance.”

“Co-founder at Skarbe who built “Oskar,” an autonomous sales agent that handles inbound email, lead qualification, and automated follow-ups using a multi-agent architecture (OpenAI Agents SDK) with a human-in-the-loop learning phase for reliability. Also owned scaling and reliability of Gmail/Outlook sync, including a Node.js-to-Rails migration and incident response during a Product Hunt launch that generated hundreds of signups and a ~2M-email queue.”

“Full-stack .NET/Azure engineer with end-to-end ownership of policy management microservices (React/TypeScript + C#/ASP.NET Core + Kubernetes) delivering significant performance and quality improvements (e.g., response time -35%, defects -30%, CSAT +18%). Also productionized an AI-assisted analyst workflow using Azure OpenAI with a RAG pipeline on Azure Cognitive Search, including rigorous prompt versioning, guardrails, and measurable impact (review time -40%, errors -55%). Led incremental legacy modernization via Strangler Fig and dual-write migrations with zero production regressions.”

Hammad Ur Rahman

Screened

Senior DevOps Engineer specializing in cloud infrastructure and CI/CD

Boston, Massachusetts11y exp

“IBM Power/AIX engineer who has owned a 150+ LPAR AIX 7.x estate with VIOS/HMC/vHMC and PowerHA in production, including real outage and failover recoveries. Also brings modern DevOps/IaC experience—built Jenkins pipelines deploying to AKS and implemented Terraform on AWS with remote state, locking, and drift management.”

JUNG NO

Screened

Senior Solutions Engineer & Applied AI Builder specializing in agentic workflows

Remote, US9y exp

“Built and shipped a production AI booking/quoting system for a Spanish-speaking cleaning business serving English-speaking customers, covering the full booking and payment flow and generating bilingual SEO/AEO content. Uses Gemini/Genkit with multi-agent orchestration (ADK/MCP, LangChain) and a production stack on Vertex AI + Cloud Run + Terraform, with analytics wired from Google Analytics to BigQuery for measurable agent performance.”

Jyothsna V

Screened

Mid-level Backend Software Engineer specializing in Python/FastAPI and cloud-native microservices

USA4y exp

“Backend engineer who evolved Coca-Cola bottlers' Trade Promotion Optimization platform at Coke One North America, building domain-focused microservices in Node.js and Python (Flask/FastAPI) with PostgreSQL. Experienced in multi-tenant security (OAuth2/JWT, RBAC, row-level scoping by bottler/region), API contract/versioning discipline, and Azure DevOps-driven incremental rollouts with strong observability.”

“Unity mobile game developer (10+ years) who has shipped 15+ iOS/Android titles (including Word Collect, Trivia Start, Word Nut, Hot Las Vegas Slots). Built a large-scale adventure/quest progression feature with 1000+ quests using procedural map generation, UI virtualization for mobile memory constraints, and a server-driven, spreadsheet-importable configuration system that became a reusable standard across games. Based in San Diego (PST) and targeting $155k USD; open to contract or full-time.”

“Built and deployed a full-stack web product for international football fans visiting the U.S. for FIFA, owning everything from crawling and aggregating event data to frontend, backend, deployment, and maintenance. Particularly strong in data-heavy product work, using LLMs, Google Maps API, and SQL/RPC patterns to improve data quality, speed implementation, and support a polished user experience.”

“Full-stack product engineer at AllCheer who has shipped production AI workflow systems in a compliance-sensitive healthcare operations context. They built React/FastAPI products with LangChain and OpenAI to automate release-of-information and note-extraction workflows, delivering measurable impact including ~60% faster processing, ~$20K annual savings, and ~92% extraction accuracy.”

“Full-stack engineer with startup SaaS experience building workflow automation and case management platforms for business operations teams. Strongest in Python, TypeScript/React, and PostgreSQL, with hands-on ownership from backend architecture and APIs to production deployment on AWS; notably helped reduce manual processing and improve customer turnaround times in a high-ambiguity scaling environment.”

“Full-stack and AI systems engineer who has shipped both enterprise fintech and real-time voice AI products. At NCR, they repaired a broken transaction-fee workflow end to end using React/TypeScript, Lambda, and DynamoDB; at Lillup, they turned a research voice prototype into production infrastructure, cutting latency from 350ms to under 200ms and raising user ratings from 2.8 to 4.1. They also built an LLM side project that uses Claude and GPT to cross-review each other through structured JSON consensus rounds.”

“Frontend engineer with experience modernizing a large healthcare platform from Adobe Flex to React/TypeScript using micro frontends while keeping legacy systems live during migration. Brings strong performance tuning skills for data-heavy UIs and real-time map applications, including profiling-driven React optimization, Next.js SSR, and WebSocket-based live tracking.”

“Frontend engineer with hands-on experience building a real-time financial market dashboard at FinSight AI, handling 30+ live data streams with React, TypeScript, WebSockets, and performance-focused rendering patterns. Stands out for measurable production impact, including a 70% reduction in unnecessary re-renders, plus strong real-time visualization and UX optimization experience.”

“Backend engineer focused on real-time, event-driven systems (Java microservices) handling high-frequency data with low-latency and reliability requirements. Strong in Kafka-based asynchronous architectures, Redis caching, JVM/query tuning, and scalable deployments on Docker/Kubernetes with Jenkins CI/CD; no direct ROS/robotics experience but has closely related distributed communication patterns.”

“Full-stack engineer with strong DevOps/AWS experience who ships end-to-end React/TypeScript + Node/Python systems and operates them in production. Built an LLM-assisted recommendations workflow for a SaaS product with robust reliability controls (schema-validated JSON outputs, fallbacks, caching, monitoring) and measured impact via adoption, time saved, and override rates; also experienced delivering MVPs fast in early-stage startup ambiguity.”