Vetted Rate Limiting Professionals

“Currently at Uplift AI shipping production LLM features that generate personalized growth insights from user reflections using BERT + embeddings + RAG, with strong safety/guardrail practices for sensitive contexts. Also built an end-to-end React Native UGC challenge submission/moderation system that improved repeat submissions and 7-day retention, and has applied rigorous clinical-style evaluation methods on a dental X-ray disease detection project to reduce false negatives.”

“Built and owned an end-to-end Python/Postgres job-tracker backend that scrapes job postings (including LinkedIn) using Selenium-driven real-browser automation, with deduplication and data-quality filtering. Has practical experience migrating deployments from DigitalOcean to Vercel and emphasizes documentation, roadmapping, and testing as part of an iterative delivery cycle.”

“Backend lead at a stealth startup and builder of MailIQ/MailBox—an automated Gmail inbox digest + cleanup system. Designed secure multi-account email ingestion and cost-efficient LLM-based summarization, and implemented robust unsubscribe automation using Playwright + OpenAI webpage analysis (including captcha-handling) with strong safety guardrails, incremental rollouts, and rollback strategies.”

“Backend engineer who rebuilt and refactored high-traffic systems at Phenom using Java/Spring Boot/Play and also designs Python/FastAPI services. Focused on measurable reliability and performance gains through DB/query optimization, async processing, and strong observability, with disciplined rollout practices (feature flags, parallel runs, rollback) and security patterns including token auth and row-level security.”

“Backend engineer with hands-on experience modernizing a real-time logistics/tracking platform from a tightly coupled polling architecture to a service-oriented/microservices design using Node.js and WebSockets. Emphasizes contract-first FastAPI development, defense-in-depth security (JWT/OAuth, RLS/Supabase), and safe incremental migrations with feature flags and strong observability, delivering sub-second updates and improved performance under peak load.”

“Built a production-grade LLM evaluation and regression system that stress-tests models across hundreds of iterations, combining LLM-as-judge, semantic similarity, statistical metrics, and rule-based checks, with results delivered via stakeholder-friendly HTML reports and dashboards. Experienced orchestrating multi-agent RAG workflows using LangChain/LangGraph and event-driven GenAI pipelines in n8n integrating OCR, speech-to-text, and external APIs, with strong emphasis on reliability, observability, and explainable failures.”

“Frontend lead for B2B SaaS products, owning React + TypeScript architecture end-to-end and scaling complex dashboards/workflows with a feature-based structure, shared design system (Tailwind), and strong quality automation. Experienced shipping high-impact features quickly using incremental delivery, feature-flagged rollouts, and performance profiling/optimization to keep production stable as usage grows.”

“Backend/full-stack engineer with experience building customer-facing contact-center automation (agent assignment) and internal editorial/data operations APIs for life-sciences ontology management. Strong in microservices and event-driven systems (Spring Boot + Kafka), third-party integrations (Genesys/Five9), and pragmatic iteration via MVP scoping, tight stakeholder demos, and observability-focused reliability.”

“Backend engineer who evolved and migrated a real-time smartwatch telemetry ingestion/analytics platform in a healthcare context, focusing on reliability under poor network conditions. Experienced with Python/FastAPI and Java microservices, PostgreSQL performance tuning, and production-grade security (JWT/OAuth, RBAC, RLS) with incremental rollout and parallel-run migration strategies.”

“Backend/AI engineer in construction tech (HyperWater AI) who delivered major production performance wins (analytics API from ~1 hour to 0.5s) and shipped LLM features for parsing subcontractor manifests into CSI divisions with human-in-the-loop review. Also built a freelance agentic document-verification system using OCR + RAG over pgvector with robust retry/escalation logic and user feedback loops.”

“Full-stack engineer who has shipped and operated generative-AI chat/QA features end-to-end, including a RAG-based pipeline with guardrails and cost/latency monitoring in production. Experienced with React/TypeScript + Node/Postgres architectures, Dockerized deployments to AWS (EC2) via GitHub Actions CI/CD, and building reliable ingestion/ETL systems with idempotency, backfills, and reconciliation.”

“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.”

“Built production LLM-driven products including a job-hunt AI (job ranking + resume optimization) and an InterviewAI agentic pipeline using LangChain. Focused on practical deployment concerns like securing OpenAI usage via rate limiting and tiered quotas, and demonstrates an applied approach to choosing models, retrieval methods (RAG), and prompting strategies.”

“Software engineer who builds workflow-centric products end-to-end, including a customer-facing module on the Trident AI content platform and an internal content workflow tool adopted as the default process. Strong in TypeScript/React + FastAPI architectures and in scaling event-driven microservices with RabbitMQ, emphasizing reliability (idempotency, DLQs) and observability (correlation IDs) to reduce outages and debugging time.”

“GEODNET engineer specializing in edge-to-cloud, real-time GNSS data pipelines at global scale (thousands of heterogeneous base stations). Built deterministic-latency ingestion with RTCM/MSM normalization, jitter buffering, and firmware-aware parsing, and shipped production hotfixes using canary rollouts and deep observability. Also delivers customer-specific GNSS/RTK outputs via tested Python tooling (CLI/API) and collaborates on-site with operators to resolve firmware and network-driven issues.”

“Senior backend/data engineer who has built and maintained HIPAA-compliant, real-time clinical FastAPI services on AWS, orchestrating ML/LLM and vector DB calls with strong reliability patterns (auth, timeouts/retries, graceful degradation, idempotency). Also delivered AWS IaC/CI-CD (Terraform/Helm/GitHub Actions) across EKS/Lambda/SageMaker and built Glue/Spark ETL with schema evolution and data quality controls, plus demonstrated large SQL performance wins (15 min to <9 sec) and hands-on incident ownership.”

“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.”

“Built and shipped "OnCall Copilot," a production Slack-based RAG assistant that answers on-call questions from runbooks and postmortems with citations using a FAISS vector index. Emphasizes reliability and measurable performance via strict guardrails ("no evidence, no answer"), evaluation metrics, drift monitoring, and operational hardening with Docker, logging, health checks, and offline fallback.”

“Unity game developer with hands-on gameplay AI experience (FSM-driven monsters with customized NavMeshAgent movement) focused on creating readable, high-tension survival encounters through iterative tuning. Has shipped/created 4 Unity games solo end-to-end (UI, animations, architecture, state machines) and has also built a full Python game server; some exposure to Photon Fusion and strong client/server REST API implementation experience.”

“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.”

“Frontend/fullstack lead who inherited a messy psychological app with production issues, drove a rapid stabilization (2–3 weeks) and major performance/architecture overhaul (Redux Toolkit, memoization, caching, lazy loading, CDN offload to S3/CloudFront). Also owns delivery and infrastructure practices (multi-env, Docker, GitHub Actions CI/CD, AWS ECS + load balancing) and led a 1-week POC for an AI-powered trucking management system (app.neblo.ai).”

“Backend/platform engineer who has owned FastAPI microservices for analytics/ML ingestion and driven measurable performance gains (cut latency ~40%). Experienced deploying to AWS (ECS/EKS) with GitOps (GitHub Actions + ArgoCD + Helm), and has executed an on-prem to AWS migration using Terraform with parallel-run cutover and ~30% runtime improvement. Also built Kafka-based real-time user activity streaming with Prometheus/Grafana observability.”

“Customer-facing AppSec/solutions engineer with experience securing cloud-native AI/LLM deployments on Azure and Kubernetes. Led threat modeling and production hardening (Key Vault secrets migration, least-privilege IAM, rate limiting, structured logging/monitoring, LLM guardrails) and has supported retail search/catalog platforms using Elasticsearch, including performance triage and rollout playbooks that improved customer trust and enabled engagement expansion.”