Vetted JavaScript Professionals

“Built a production LLM-powered workflow at Frontier to extract structured signals from messy, high-volume documents and route work to the right teams, replacing a multi-day, error-prone manual process. Emphasizes production reliability with schema/consistency validation, re-prompting and deterministic fallbacks, plus async pipeline optimizations for predictable latency. Experienced with multi-agent orchestration (LangGraph, AutoGen, CrewAI) and AWS workflow tooling (Step Functions, SQS, Lambda), and delivered ~70% safe automation via stakeholder-driven thresholds and human review.”

“Robotics software engineer at Earthwise building a full ROS2 Humble warehouse AMR stack for bin picking—owning perception (Livox/Orbbec/RPLidar fusion + calibration), Nav2 navigation with custom planners/behavior trees, and application-layer nodes (barcode scanning, safety monitoring, web HMI). Demonstrated strong real-world debugging and performance tuning (sub-cm AprilTag docking; ~80% reduction in localization failures) plus solid simulation/CI practices (Gazebo + Docker + GitHub Actions).”

“Full-stack engineer (Devsinc) who built a seed-stage fintech product (Deaglo) for global investment firms, shipping a real-time FX exposure and hedging dashboard using Next.js App Router + TypeScript with Python/C# microservices. Drove major reliability and performance wins by migrating to an async RabbitMQ architecture (DLQs, idempotency) and optimizing Postgres queries (45% faster), while owning monitoring and post-launch backlog.”

“Full-stack engineer (React/TypeScript + Bun/Node-like backend) who recently rebuilt a terminal-based chat UI, implementing custom Markdown lex/parse/render and a typewriter-style streaming renderer while optimizing React DOM growth for ~50% faster performance. Has startup experience making high-ownership decisions under ambiguity and rapidly integrating multiple external AI/tooling services (5–6 in a week) with fallback strategies for flaky dependencies.”

“Software engineer who shipped an end-to-end internal workforce dashboard at Northwestern Mutual, spanning Spring Boot APIs, PostgreSQL schema/query optimization, and a React + TypeScript UI with role-based access and filtering. Has hands-on production experience deploying via GitHub Actions CI/CD to AWS (Docker, EC2, RDS) and resolving performance incidents by tuning database queries and indexes.”

“QA automation engineer with strong Cypress/JavaScript experience in healthcare claims and eligibility systems, owning end-to-end regression suites that combine UI, API, and SQL/database validations. Known for catching subtle pricing/benefit calculation defects (copay/deductible/accumulator issues) before release, stabilizing flaky CI tests via API synchronization, and shaping requirements early to improve testability and reduce downstream rework.”

“Backend engineer who built and scaled a transaction-processing microservice (150K+ records/day) in a microservices ecosystem, debugging peak-load latency/timeouts via CloudWatch/Grafana, Kafka lag analysis, and DB query tuning (indexes, Redis caching, batching). Also shipped an LLM-powered document assistant end-to-end with prompt/response validation plus retries/fallbacks for production reliability.”

“Software intern at BestWork who owned an AI-powered sales performance chatbot end-to-end: React/Material UI frontend, TypeScript AWS Lambda backend, and AWS Bedrock (Llama 3) + OpenSearch knowledge base over Salesforce/HubSpot data with Slack-based weekly summaries. Worked directly with the CTO in a high-ambiguity environment, including building an audio bot from scratch just in time for a client demo, and implemented metadata-based retrieval to handle multi-team knowledge base constraints.”

“Governance engineer intern at GSK who built policy-as-code automation using Open Policy Agent/Rego integrated into GitHub CI/CD and Terraform workflows. Also built and shipped a voice-enabled expense tracking app using speech-to-text + LLM structured extraction with strong validation, retries, and semantic guardrails, and designed the supporting PostgreSQL data model with performance-focused indexing.”

“Software/data engineer who has shipped internal platform features end-to-end, including a widely used CSV export tool with synchronous + async flows on AWS that reduced timeouts and improved database access security. Also built a high-volume pipeline processing 80M+ daily banking transactions for advertiser user categorization, and delivered a production Gemini-powered financial calculator using structured prompting and robust API error handling.”

“At Delta Airlines, built and shipped a production LLM-powered semantic search/troubleshooting assistant over maintenance logs and operational documentation using OpenAI embeddings and a vector database. Implemented hybrid ranking, query enrichment, and structured filters to improve relevance ~35% while optimizing latency via caching and vector tuning. Also designed a scalable Kafka + AWS (Lambda/SQS) ingestion pipeline with strong reliability/observability and an eval loop using real engineer queries and human review.”

“Full-stack engineer with cloud and GenAI experience who has owned production features end-to-end, including a reporting dashboard optimized from 14s to 5s using query/API refactoring and monitored via AWS CloudWatch. Also productionized an OpenAI-powered chatbot using LangChain with prompt design, guardrails, and evaluation via production logs and user feedback, and has led incremental legacy-to-microservices modernization with parallel run to avoid regressions.”

“TSE with hands-on experience troubleshooting customer-reported data issues across APIs and SQL, coordinating with engineering on hotfixes, and translating risk to non-technical stakeholders. Has supported application security workflows using Veracode by generating reports, driving remediation via Jira, and tracking exposure metrics; also assisted customers with SSO setup (client ID/secret).”

“Backend engineer who has shipped both high-throughput real-time systems and production LLM/RAG features. Built a database-free, local-first messaging service (Node/Express/Socket.IO) achieving ~1,500 msgs/sec at <25ms p95, and implemented a Go-based RAG recommendation pipeline with strict JSON/schema validation, catalog grounding, fallbacks, and eval loops that cut hallucinations to ~1–2% while reducing LLM costs ~60%.”

“Backend-leaning founding/early engineer who built automation platforms end-to-end: FastAPI/Python services integrated with a Next.js/TypeScript frontend, including a production VNC streaming URL endpoint for cloud-instance desktop viewing. Also designed core Postgres user/workflow data models and built an agentic orchestration system with LangChain/LangGraph (sub-agents, validators, pause/resume), plus made scalability tradeoffs like S3 pre-signed uploads to keep microservices responsive.”

“Built and operated a real-time student event/party discovery platform with map-based search, RSVP, and authentication using React/TypeScript, Node.js, and Firebase Firestore. Demonstrates strong backend correctness under concurrency (transactions, idempotency, retries/backoff) and solid API product thinking (versioning, Swagger docs, structured errors, cursor pagination), including custom geospatial querying via Haversine filtering.”

“Backend/platform engineer with Optum experience owning a production FHIR Member Access API aligned to CMS interoperability requirements. Built and scaled Spring Boot/HAPI FHIR microservices on AWS (Docker/Kubernetes) with zero-downtime CI/CD, and operated them with strong observability (Dynatrace, logs/metrics, alerting) and incident response. Also implemented a Kafka-based FHIR bulk data pipeline with schema versioning, idempotent processing, and reliable backfills/replays.”

“Consulting-style LLM practitioner who builds enterprise knowledge assistants using RAG and takes them from prototype to production with guardrails, evaluation, and full-stack observability. Experienced partnering with IT and customer-facing teams to demo solutions, build tailored prototypes, and drive adoption through API-based integration.”

“Backend/data engineer with experience at Assurant and Capgemini, focused on reliability and performance at scale. Improved high-latency backend APIs by adding and iterating on a Redis caching layer driven by CloudWatch/monitoring metrics, and built scalable BI pipelines that normalize messy multi-source enterprise data with strong observability and error handling. Familiar with LLM/RAG architecture and practical guardrails, though has not yet shipped an LLM feature to production.”

“Full-stack engineer who built an end-to-end low-code/no-code IDE for creating AI/ML workflows for industrial IoT sensors using Next.js/TypeScript and NestJS microservices. Focused on scaling high-volume sensor dashboards—improved UX and performance via WebSockets, debouncing, pagination, and API payload reduction—validated with profiling tools and user feedback in a startup environment.”

“Frontend-focused engineer with enterprise Angular experience integrated with .NET APIs, emphasizing production-ready practices (reusable components, modular architecture, TypeScript standards, Jasmine unit tests, and CI/CD). Has not built Unreal Engine UI systems yet, but articulates how they would translate web UI modularity, separation of concerns, and testing/automation practices to Unreal/CommonUI workflows.”

“Software engineer with medical-domain experience at Philips focused on end-to-end systems integration and reliability, including integrating C# xUnit automated test suites with backend services and CI-driven staging deployments. Also built a Python/scikit-learn typing speed analyzer integrating data collection, model training, and a real-time user interface; interested in transferring this systems/debugging rigor into robotics despite no ROS/robotics project experience yet.”