Vetted TypeScript Professionals

“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.”

“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.”

“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.”

“Full-stack/AI engineer who has shipped production systems spanning real-time analytics dashboards and an internal LLM-powered knowledge assistant. Experienced with RAG pipelines (embeddings/vector DB, semantic retrieval, query rewriting) plus evaluation loops and guardrails, and builds observable Kafka-based data pipelines monitored with Prometheus/Grafana.”

“Built multiple systems from scratch at DSSD and Aglint, including an NGO sustainability reporting dashboard and a production LLM-powered phone screening agent using Twilio/Retell AI with RAG grounded in PostgreSQL candidate/job data. Strong focus on real-world reliability: guardrails, monitoring, and lightweight eval/regression loops that reduced recruiter score overrides by ~30%. Currently on OPT through May 2026 (plans STEM OPT extension) and committed to relocating to NYC for in-person work; seeking $90k–$120k base with meaningful equity for founding engineer roles.”

“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.”

“Built core perception and decision layers for a 3D AI-powered interactive avatar/agent with a robotics-like perception–reasoning–action loop, combining computer vision, NLP, and real-time response. Focused on making multimodal inputs robust (normalization, intent + emotion signal fusion) and improving real-time performance via instrumentation, profiling, and parallelization; also designed distributed, loosely coupled state-based communication and deployed services with Docker.”

“Backend engineer experienced in evolving high-scale legacy on-prem systems into cloud-native, event-driven microservices on AWS/Kubernetes (noted peak traffic ~1.5M QPS). Strong focus on reliability engineering and operational excellence—SLO-driven observability, GitOps/canary rollouts, chaos testing, and preventing cascading failures (e.g., retry-storm mitigation).”

“Robotics/AV-focused candidate who contributed to an F1TENTH autonomous vehicle college project, building key autonomy components from raw sensor data to driving commands. Strong in perception and state estimation (visual odometry, particle-filter localization), plus mapping (occupancy grids) and planning/control (RRT, Gap Follow, PID), with hands-on ROS tooling and simulation validation in Gazebo/RViz and ROS environment containerization using Docker.”

“Built Meet.AI end-to-end and made concrete architecture/performance decisions (RPC with type-safe integration; SSR + query prefetching for instant data display). Also created a Python tool at Abbott to resynchronize Ansible inventories and eliminate manual intervention by scheduling it in a Jenkins pipeline; has hands-on Docker/microservices experience including serving a pretrained LLM.”

“Backend engineer with legal-tech and AI workflow experience: built JurisAI, an end-to-end legal research system using OCR + embeddings + Pinecone vector search to deliver citation-grounded LLM answers with safe failure modes (~90% recall@K). Also led a GW Law metadata migration into Caspio with batch validation and parallel rollout, and has strong FastAPI/GCP production reliability and observability practices.”

“Robotics software engineer who built the perception-to-planning pipeline for an autonomous bipedal robot: synchronized and fused 3D LiDAR + multiple depth cameras in ROS1 (tf2/message_filters) to produce combined point clouds and 2.5D maps, then implemented and benchmarked A*/D*/RRT plus hybrid A* footstep planning in simulation. Also founded a software company and personally owned CI/CD, security checks (CodeQL), and release automation (custom release bot + Slack notifications).”

“Backend/data engineer who has built production AI video generation services on AWS using a hybrid serverless + container architecture (FastAPI, Lambda, ECS, Postgres/Redis) with strong reliability practices (auth, retries/timeouts, structured logging, CloudWatch + Slack alerting). Also delivered AWS Glue ETL pipelines with schema evolution handling and modernized a legacy SAS healthcare reporting workflow to Python with parity validation and parallel-run migration.”

“Built and owned invoice automation and alerting products at Neuralix, automating multi-site electricity invoice ingestion from PDFs into validated JSON with strict schema enforcement and LLM-based validation (reported ~98% compliance). Delivered zero-manual processing at 200+ invoices/month and ~5x faster throughput, and designed a domain-driven alert lifecycle to reduce noisy notifications and improve operational response.”

“Full-stack engineer who built an AI-based inventory/procurement query system at Botlily/Botlerly using Flask and Google Sheets as a live knowledge base, overcoming Sheets latency with caching and structured in-memory models. Demonstrated strong LLM product engineering (40% accuracy improvement via preprocessing/prompting) and customer-driven iteration with bar/restaurant owners, evolving the tool into a more comprehensive inventory management and forecasting solution.”

“Frontend product builder who has shipped and maintained a two-mobile-app ecosystem (user + employee) backed by Node.js, emphasizing separation of concerns, shared libraries for reuse, and TypeScript type safety. Re-architected a Sunmor Research codebase using MVC, improving readability and collaboration and taking the product from unusable to working, with a strong regression-testing mindset and customer-feedback-driven iteration.”

“Frontend engineer who led an MVP-to-scale React/TypeScript web dashboard for high-volume email triage with AI-suggested replies, supporting multi-tenant Gmail/Outlook providers. Emphasizes rigorous state normalization and layered state management (React Query + workflow + local UI), plus a testing-pyramid QA strategy and measurable performance instrumentation to keep quality and velocity high.”

“Built and deployed “ApartmentFinder AI,” a multi-agent system using Google ADK, Gemini, and Google Maps MCP to automate apartment shortlisting and commute-time analysis, cutting a 45–70 minute user workflow down to ~30 seconds. Also has strong delivery/process chops from serving as an SDLC Release Coordinator, managing 52+ releases and reducing SDLC issues by 84%.”

“Led an end-to-end build of bhangrascape.ca, making key architecture choices across Next.js/Node/Postgres on AWS and implementing S3-based media storage with presigned URLs. Strong focus on quality and reliability via Zod validation, Jest tests, Postman endpoint testing, and CI/CD with GitHub Actions, plus hands-on UX ownership from Figma prototyping through reusable React components and A/B testing.”

“At Trellis, built and shipped a production multi-agent, authenticated GenAI chatbot for sensitive financial account inquiries (loan/payment lookups), using dynamic model routing to control latency and cost while improving accuracy. Implemented prompt-injection defenses (Meta Prompt Guard), RAG with LangChain, and LLM-as-a-judge evaluation; the system cut manual support call volume by 40%+ and was refined through close collaboration with QA-driven user testing.”

“Full-stack TypeScript/React/Next.js builder who created an end-to-end customer-facing product (AI Job Master) that generates personalized outreach from resumes and job descriptions. Demonstrates strong product + engineering ownership with rapid MVP iteration, instrumentation-driven prioritization, and pragmatic reliability patterns (microservices, queues, correlation IDs, retries) while tackling a key AI challenge: user trust and output consistency.”

“Frontend-focused engineer with internship experience at eXp Realty and Pulse InfoFrame, building survey platforms and a drag-and-drop survey management UI in React + TypeScript. Notably helped execute a post-deployment migration from DynamoDB to Amazon RDS to enable scalable SQL aggregation (tested with ~70k survey instances), and monitored rollout via CloudWatch/Cloudflare logs while driving QA and load testing.”

“Founding engineer at a startup building LLM/agentic workflows for public-safety customers, with hands-on experience delivering a hybrid on-prem + secure cloud solution to meet strict compliance needs. Implemented OpenTelemetry observability for multimodal agentic systems behind closed networks and used the resulting traces to optimize prompting/token usage for customer-specific security integrations. Regularly runs technical workshops and supports pre/post-sales by translating integration feedback into product roadmap decisions.”

“Full-stack engineer with recent enterprise experience building Spring Boot/Spring Cloud microservices on AWS (Lambda, S3, DynamoDB) and a React/TypeScript frontend. Has hands-on experience solving microservice communication timeouts via API Gateway/load balancing and implementing centralized JWT-based security, plus performance work for large data workloads using indexing, caching, and async processing.”