Vetted HTML Professionals

“Built and deployed a production LLM-powered multi-agent compliance copilot (life sciences/finance) using LangChain/LangGraph + RAG over vector databases, delivered via async FastAPI on Kubernetes. Emphasizes audit-ready, deterministic outputs with schema constraints and citations, plus rigorous evaluation/monitoring; reports 60%+ reduction in manual research time and successful production adoption.”

“Full-stack engineer who has owned customer-facing AI recommendation and analytics dashboards end-to-end (backend APIs/data processing through React UI, deployment, and monitoring). Demonstrates strong systems thinking around scaling microservices—using observability, caching, async workflows, and resilience patterns—and also built an internal ops dashboard that became the default tool for on-call incident reviews.”

“Frontend engineer with senior-level scope who has shipped complex React/TypeScript products end-to-end, including a multi-page site built solo in four weeks (complex forms, PDF generation, email + localization) and a GraphQL-driven dashboard for a car dealership management platform. Known for modular, testable architecture, performance-minded data fetching (batched calls), and improving design-system consistency via reusable, Storybook-documented components and feature-flagged rollouts.”

“Backend-focused engineer who built a resume processing and job application platform using Python/MongoDB/Streamlit, including OpenAI-powered skill/keyword extraction and recruiter-facing search/filtering. Has hands-on cloud deployment experience on AWS/Azure and executed an on-prem reservation portal migration to Azure using a phased trial-and-cutover approach; also automated CI/CD with Jenkins and GitHub Actions.”

“Cloud-focused engineer experienced deploying and stabilizing complex production systems that span APIs, infrastructure, and automated workflows, with a strong observability and safe-release mindset (feature flags/canaries/rollbacks). Has hands-on, customer-facing incident leadership, including executing DR regional failover during an AWS us-east-1 outage to maintain service and reportedly save a client ~$10M.”

“Robotics software engineer who built and owned core navigation components for a TurtleBot in ROS/ROS2 and Gazebo, including an RRT-based planner, waypoint-to-velocity motion planning, and PID trajectory tracking. Demonstrates strong real-time debugging skills (control-loop timing under CPU load), costmap/occupancy-grid tuning, and distributed ROS2 communication design using DDS/QoS, plus Docker and CI/CD automation experience from Keysight.”

“Backend engineer with hands-on IoT and AI product work: built a decoupled Raspberry Pi + AWS IoT Core weather monitoring backend and a Dockerized FastAPI LLM service on AWS ECS using OpenAI/HuggingFace with an emerging RAG layer. Also delivered measurable performance gains at DAZN by redesigning event-driven/serverless ingestion (SNS, S3->Lambda->DynamoDB), cutting latency ~30% and boosting throughput ~25% while automating ~90% of manual sync work.”

“Built a production GenAI-powered analytics assistant to reduce reliance on data analysts by enabling natural-language Q&A over Databricks/Power BI dashboards, backed by vector search (Pinecone/Milvus) and a Neo4j knowledge graph, including multimodal support via OpenAI Vision. Demonstrates strong real-world LLM reliability engineering with strict RAG, LangGraph multi-step verification, and Guardrails/custom validators, plus broad orchestration and production monitoring experience (Airflow, ADF, Step Functions, Kubernetes, Prometheus/CloudWatch).”

“Backend/full-stack engineer building complex internal platforms and customer-facing demos at the intersection of infrastructure and product. Shipped a no-code Product Lifecycle Manager for manufacturing (3 manufacturers, 1000+ evolving tests) using AWS S3/SQS ingestion and extensible Postgres (EAV+JSONB) with end-to-end traceability. Also built a FastAPI-based company data intelligence platform with Okta-secured RBAC and an LLM/MCP layer for ChatGPT-like analytics over enterprise data sources.”

“Software engineer with strong compliance-domain experience who built a customer-facing compliance and reporting dashboard using React/TypeScript with Spring Boot microservices. Demonstrates mature production engineering practices—contract-first APIs, event-driven architecture (Kafka/RabbitMQ), caching (Redis), and robust CI/CD + observability (Prometheus/Grafana/ELK)—and also created a Python-based audit automation tool adopted into the standard release process.”

“Product-focused full-stack engineer with Walmart and Dell experience who built and shipped a real-time engagement dashboard end-to-end (Kafka Streams, Spring Boot, React/TypeScript/D3) used daily by business teams, moving them from next-day reports to real-time decisioning. Strong in performance/reliability (Redis caching cut latency ~40%, 90%+ test coverage, Prometheus/CloudWatch monitoring) and production operations on AWS/EKS including handling a cascading failure from a memory leak with zero-downtime rollback and redeploy.”

“Full-stack engineer with production experience building and owning high-traffic e-commerce checkout flows in Next.js (App Router) + TypeScript across microservices (REST/GraphQL). Demonstrated measurable performance wins (30% checkout improvement; 85% initial load reduction at 20th Century FOX) and strong production rigor (APM/logs, CloudWatch, Postgres indexing + EXPLAIN ANALYZE), including offloading PDF generation to AWS Lambda.”

“Full-stack engineer with hands-on experience building and owning production e-commerce features in Next.js (App Router) + TypeScript, including SSR-driven category browsing with pagination and region-specific pricing. Strong focus on post-launch reliability and performance—optimizes React rendering (lazy loading/Suspense), tunes Postgres queries with indexes/explain plans, and supports durable order-processing workflows with idempotency, retries, and structured logging.”

“Full-stack engineer with experience at T-Mobile, Cisco, and Bharti Airtel, owning production plan upgrade/billing flows end-to-end from React/TypeScript UI through Spring Boot services to Docker/Jenkins/Kubernetes deployments. Demonstrated reliability and performance wins by migrating synchronous service calls to Kafka-based async processing with circuit breakers and by tuning Postgres queries/connection pools, achieving a reported 25% API response-time improvement and faster incident resolution via improved observability.”

“JP Morgan engineer and Texas A&M student web developer who has owned production systems end-to-end, including a real-time ML training workflow that improved internal search relevance by 30%. Experienced with AWS cloud migrations and operating containerized services on ECS with CloudWatch+ELK observability, Terraform infra, and Spinnaker CI/CD; also built event-driven pipelines with RabbitMQ and Elasticsearch at 1M+ record scale.”

“Software engineer with experience across enterprise (AIG, MSCI) and an early-stage startup (Job Map), owning production systems end-to-end. Built secure insurance microservices on Spring Boot with JWT/RBAC and AWS-based CI/CD/observability, plus Kafka streaming pipelines for financial data. Also shipped a GenAI personalization MVP using FastAPI and LLM APIs in a high-ambiguity startup environment.”

“Software engineer with Intuit experience shipping an end-to-end real-time financial insights product on AWS, using event-driven architecture with Kafka and Spark Streaming to process millions of records with low latency. Also delivers customer-facing React + TypeScript dashboards and has hands-on production operations experience, including resolving a database scaling incident via read replicas, query tuning, and connection pooling.”

“Software engineering intern at China Telecom who built and continuously evolved a real-time transaction platform ("Smart Tangerine") focused on strong consistency and peak-hour concurrency. Implemented microservices with Redis and RabbitMQ to decouple heavy processing and cut latency (~80ms to ~30ms), and led a zero-downtime migration from a monolith using strangler pattern, dual-write, and traffic shadowing.”

“Backend/data engineer who has built production Python microservices (FastAPI) and AWS-native platforms for event ingestion and analytics, combining ECS/Fargate + Lambda with CloudFormation-driven environments and strong secrets/IAM practices. Experienced modernizing legacy logic with parallel-run parity validation and safe phased cutovers, and has demonstrated measurable SQL tuning wins (20–30s down to 1–2s) plus incident ownership in Glue/Step Functions ETL pipelines.”

“Worked on Sophia the humanoid robot, building production animation pipelines and enhancing human-robot interaction via perception and behavior orchestration. Experienced in stabilizing noisy perception-driven state transitions and designing smooth, user-centered behavioral flows, collaborating closely with artists, animators, and experience designers to translate creative intent into measurable system behavior.”

“Backend/platform engineer with experience across C3.ai (supply chain demand planning) and Amdocs (telecom), working on large-scale data systems and microservices. Has driven first-time adoption experiments of Snowflake + Spark to handle billion-record workloads, built Jenkins-to-Kubernetes delivery pipelines with Nexus artifact management, and implemented Kafka streaming between microservices with HA and retry/error-handling patterns.”

“Distributed-systems engineer applying robotics-style patterns to software: built "Vibecheck," a high-throughput real-time video + OS-telemetry fusion and analysis system (500+ MB/session) with strict latency constraints. Strong in containerization and CI/CD (Docker, GitHub Actions) and in designing fault-tolerant, event-driven architectures (Kafka/RabbitMQ), plus hands-on debugging of multi-agent coordination using blackboard + watchdog/circuit-breaker control patterns.”

“LLM/RAG engineer who has built and deployed corporate-scale systems at Novartis and Johnson & Johnson, including a healthcare AI agent that generates day-to-day treatment schedules. Recently handled a high-stakes safety incident (LLM suggesting overdose) by tightening model instructions and validating with ~200 test prompts, and has strong end-to-end data/embedding/vector DB pipeline experience (PySpark, FAISS, Pinecone) plus SME-in-the-loop evaluation (RLHF).”