Vetted REST APIs Professionals

“AI/back-end engineer at Canon who helped build and operate an internal production LLM platform that acts as a secure middle layer between users and models, defending against jailbreaks/prompt injection while enabling RAG, memory, and grounded responses over company data. Experienced with LangChain/LangGraph orchestration, vector DB retrieval, and reliability practices (testing, monitoring, adversarial prompts) to run high-throughput, low-latency AI workflows in production.”

Tanya Parker

Screened ReferencesStrong rec.

Senior Frontend Developer specializing in WebXR and Three.js

London, UK9y exp

“XR professional with 9 years in the industry and 3 years using Unity; built a solo Unity city-building/resource management game (BLEAK) inspired by Anno in a dystopian cyberpunk setting. Has shipped web-based XR experiences (not Unity headset titles) and emphasizes pragmatic scope control and production adaptability, honed further during time at Zappar.”

“Full-stack engineer who built a custom LMS end to end with Next.js, TypeScript, Python, AWS, and S3, owning the learning module experience and structured progress tracking. Also shipped a bilingual English-Swahili caregiver support WhatsApp chatbot using OpenAI, with strong attention to safety boundaries, anonymous logging, prompt iteration, and real-world deployment in a sensitive support context.”

“Engineer focused on real-time collaborative canvas products and AI-assisted design workflows, with hands-on ownership of both multiplayer infrastructure and LLM-powered generation systems. They combine strong TypeScript/full-stack architecture with production-grade AI evals and observability, and cite meaningful outcomes including zero sync-conflict bugs, rollout to 50,000+ DAUs, and major gains in onboarding speed and engagement.”

“Frontend-focused engineer with full-stack capability (Node/Express + MongoDB/MySQL) who emphasizes scalable quality practices: PR-driven reviews, CI quality gates, and a full testing pyramid (Jest/Vitest, React Testing Library, Cypress/Playwright). Built complex React + TypeScript role-based dashboards/workflows using reusable component architecture and layered state management (React Query/SWR, Context for auth/roles), with strong performance and UX polish (Lighthouse, lazy loading, accessibility, responsive design).”

“Built a production-grade, semi-automated document recognition and classification system for large volumes of scanned PDFs, starting from little/no labeled data and handling highly variable scan quality. Deployed on AWS using SageMaker + Docker and orchestrated on EKS with a microservices design that scales CPU-heavy OCR separately from GPU inference, with strong reliability controls (validation, fallbacks, retries, readiness probes).”

“Software engineer who deployed and stabilized a real-time analytics platform at Senecio Software, focusing on production reliability, observability, and performance under load. Experienced debugging issues spanning distributed services and networking (e.g., tracing timeouts to packet loss from misconfiguration) and extending Python (FastAPI/Django) APIs for customer-specific analytics features in a configurable, maintainable way.”

“LLM/agentic AI builder who deployed a production ITSM automation agent on Google ADK integrating ServiceNow and FreshService, with strong safety guardrails (human-approval gating and runbook-only command execution) and rigorous evaluation (500 synthetic tickets; 80%+ false-positive reduction). Also partnered with finance to deliver an AI agent that automated invoice/SOW retrieval and monthly reporting to account managers, reducing manual back-and-forth.”

“Built and deployed a production-grade, multi-agent Text-to-SQL assistant that lets non-technical stakeholders query large enterprise databases in natural language. Uses Pinecone-based schema retrieval + LLM reasoning (Gemini/Claude/GPT) with a dedicated validation agent (schema/syntax checks and safe dry runs) to reduce hallucinations and improve reliability, while optimizing latency and cost via async execution and embedding caching.”

“Full-stack/product-leaning engineer in logistics and high-traffic portals who ships production AI features: built an AI-assisted shipment status Q&A system using Pinecone + GPT-4 and a high-volume Python ingestion pipeline (500K+ records/day), delivering 35% fewer support tickets and cutting resolution time from 11 to 4 minutes. Also led a legacy Angular-to-React/TypeScript rebuild that boosted Lighthouse performance from 60 to 90, and has hands-on AWS EKS operations experience including resolving a 3x traffic scaling incident.”

“Backend Java developer who built an end-to-end upcoming payments feature: Spring Boot/Hibernate microservices with MySQL query/index optimization and Kafka event publishing, plus a web UI timeline component enabling users to view, skip, and edit scheduled payments with clear status indicators.”

Abdul Rehman

Screened

Senior Software Engineer specializing in Node.js/NestJS and FinTech platforms

Lahore, Pakistan8y exp

“Frontend engineer who led end-to-end development of the Neelum transportation admin panel (React + TypeScript + AntD), building scalable dashboards and multi-step workflows for users/roles/bookings/operational zones. Emphasizes maintainable feature-based architecture, typed API contracts, performance optimization for data-heavy UIs, and disciplined quality/rollout practices (regression checks, feature flags) in fast-paced environments.”

“Production-focused ML/AI engineer with hands-on ownership across classical ML and GenAI systems, from CV/NLP services to enterprise RAG. Stands out for combining research-to-production execution with measurable business impact: 40% processing-efficiency gains, 35% fewer support tickets, 5x latency improvement, and 3x throughput gains while maintaining safety and quality.”

“Built Python-based data workflow integrations for a Huntsman Cancer Institute research project, focusing on reliable upload, validation, processing, and retrieval of messy research data. Demonstrates strong practical instincts around automation hardening, observability, and translating ambiguous manual processes into structured workflows, including Selenium automation when APIs were unavailable.”