Vetted JSON Professionals

Anthony Thanpoovong

Screened

Entry-level Software Engineer specializing in cloud, AI, and full-stack development

Toronto, Canada1y exp

“Backend/AI engineer with hands-on experience building LLM-powered data products and AI platform workflows, including a project that turns tabular datasets into graphs, summaries, and chat-based insights with 1-2 second latency. Also contributed at TELUS to a Sovereign AI Factory self-serve onboarding platform tied to 100+ NVIDIA H200 GPUs, giving them an interesting mix of applied LLM, platform, and infrastructure exposure.”

“Backend engineer in healthcare data systems who has owned production pipelines end-to-end, from ingesting patient and claims data to serving it through secure APIs. Brings a strong mix of Python, SQL, microservices, cloud deployment, and data reliability practices, with measurable performance gains and experience building resilient integrations with external data sources.”

“Frontend-leaning full-stack engineer with experience building real-time, high-stakes operational software for airport gate management and billing/analytics systems. Stands out for combining strong React/TypeScript architecture with backend and data-layer ownership, including WebSockets, SQL optimization, and analytics feature delivery in production.”

“Candidate approaches AI-assisted coding like a senior developer supervising junior contributors: they define precise technical requirements, enforce code quality and documentation, and review outputs before approval. They also actively lead multi-agent workflows using OpenClaw and a Kanban-style AI project management setup, coordinating both coding and non-technical agents.”

“Built and deployed an LLM-powered customer support assistant (“Notable Assistant”) focused on automating common post-customer queries while maintaining multi-turn context and meeting scalability/latency needs. Experienced with production orchestration and operations using Kubernetes and Apache Airflow (DAG-based ETL, scheduling, monitoring/alerts), and has partnered closely with customer service stakeholders to align chatbot behavior with brand voice through iterative testing.”

“Applied NLP/ML engineer with experience at KeyBank and Novartis building production document intelligence and entity-resolution systems in finance and healthcare. Has delivered end-to-end pipelines (Airflow + AWS) using transformers (DistilBERT/Sentence-BERT), vector search (FAISS/Milvus/Pinecone), and human-in-the-loop labeling to achieve measurable gains (40%+ faster queries; up to 88% F1 and 93% precision/90% recall in entity linking).”

“Backend/data engineer with hands-on production experience building reliable Python FastAPI services on Kubernetes and delivering AWS EKS + Terraform CI/CD with strong secrets isolation and rollback practices. Also built AWS Glue ETL pipelines into S3/Redshift with schema-evolution handling and data-quality controls, modernized legacy analytics into modular Python services with parallel-run parity validation, and has demonstrated SQL tuning impact (minutes to seconds) plus ownership of batch pipeline incidents end-to-end.”

“Backend/data engineer with hands-on production experience building FastAPI APIs secured with JWT and delivering AWS-based data processing solutions using Lambda and ECS Fargate. Has worked with Snowflake/third-party API sources and targets including DynamoDB, S3, RDS, Redshift, and Glue, and uses CloudWatch/X-Ray for monitoring and troubleshooting. Seeking ~$65/hr and is open to onsite work in Bethesda, MD.”

“GenAI/RAG engineer who has deployed a production policy/regulatory search assistant for a financial client using LangChain + Vertex AI, FastAPI, Docker/Kubernetes, and Airflow-orchestrated data pipelines. Demonstrated measurable impact with 50–60% latency reduction and 70% fewer pipeline failures, plus KPI-driven grounding evaluation (90%+ target) and strong cross-functional collaboration with compliance/business teams.”

“Software engineer/QA automation leader with Lowe’s experience owning automation quality strategy for a customer-facing platform supporting large contractor orders. Built TypeScript/React dashboards backed by Spring Boot microservices (MongoDB) and RabbitMQ async messaging, with strong CI/CD test automation and production monitoring (Prometheus/Grafana). Also created an internal automated test reporting dashboard that improved QA workflow through training-led adoption and iterative refinement.”

“Backend engineer with banking-domain experience building production microservices and Kafka-based transaction processing systems. While they have not yet shipped a full LLM agent, they bring relevant distributed-systems expertise in reliability, observability, idempotency, and event-driven workflow design, including a reported 15-20% performance improvement.”