Vetted TypeScript Professionals

“Frontend engineer who leads end-to-end delivery of complex workflow-driven React + TypeScript products on top of Rails/GraphQL backends, with a strong emphasis on typed API contracts, scalable architecture, and automated quality gates. Shipped major features (e.g., inventory reservation at Jobber) using feature-flagged rollouts, close QA collaboration, and performance-focused iteration.”

“Built an internal Meta tool (HiVA Bot) for notification customization and end-to-end task tracking around advertiser-reported issues, including chat-thread creation, org-hierarchy opt-ins, SLA reminders, and search/typeahead features. Implemented the system with a Java/Spring Boot microservices approach and asynchronous patterns, and supported adoption via internal wiki documentation.”

“Software engineer focused on reliability and scalable systems: built React/TypeScript dashboards backed by Java/Spring Boot APIs and designed Kafka-based microservices with strong contract/versioning discipline. Known for shipping incremental improvements with tight feedback loops and for creating internal observability tools that streamline on-call and incident diagnosis under high-traffic conditions.”

“Backend engineer with experience building microservice-based systems that integrate LLM workflows (code review suggestions, documentation generation, test scaffolding) using REST APIs, Celery/Redis, and OpenTelemetry for observability. Demonstrates hands-on database and performance optimization in PostgreSQL/SQLAlchemy (bulk inserts, lock mitigation, cursor-based pagination) plus multi-tenant data isolation via tenant-aware models, middleware scoping, and schema/row-level strategies.”

“Robotics-focused Python developer who built autonomous navigation for a differential-drive robot using onboard vision and AprilTag detection, including pose estimation and coordinate frame transformations for localization and motion planning. Also has practical backend performance experience using Redis TTL caching to speed responses and reduce server load, plus basic PostgreSQL query/index optimization.”

“Search/backend engineer with hands-on experience improving Apache Solr-based search systems end-to-end (indexing strategy changes, ETL updates, and Java/Spring Boot Search API work). Demonstrated production rigor with QA partnership, A/B testing, and rollback-safe kill switches, plus measurable product impact (e.g., +1.5% add-to-cart) and operational troubleshooting including traffic/security mitigation.”

“ML/LLM engineer who built production systems to speed up artist content-creation workflows, including a fine-tuned image captioning model paired with a RAG layer over image embeddings/captions to improve consistency across changing domains. Experienced orchestrating multi-tool agents with LangChain/LangGraph (planning + critic/reflection) and setting up practical monitoring (caption rejection rate) plus evaluation sets for tool-calling accuracy, output quality, and latency.”

“Full stack engineer in the financial/thematic investing domain who built end-to-end applications on AWS. Notably redesigned a slow portfolio analytics workflow by offloading heavy computations to scheduled AWS Lambda jobs and caching results in DynamoDB (TTL), cutting API latency from ~5 seconds to under 300ms while supporting data-heavy daily market processing.”

“Backend-heavy full-stack engineer with experience at Intuit (TurboTax Live) and Paytm payments, building and scaling Java/Spring Boot microservices for high-traffic transaction systems. Has hands-on wins improving peak-load performance using Redis/disk caching and Kafka event-driven patterns, plus React/Redux work for web app integration and strong monitoring practices with ELK.”

“Built a production-style PyTorch LSTM system that generates structured piano compositions from 1200+ MIDI files, then significantly improved long-range musical coherence by implementing Bahdanau attention based on research literature. Also has internship experience using Docker Compose for containerized backend workloads and has independently used Ray to scale ML experiments across multiple GPUs, including dealing with GPU scheduling/memory oversubscription issues.”

“Fintech product engineer working on a large-scale credit monitoring platform (tens of millions of users) with deep experience in regulated banking integrations, PII security, and step-up/MFA flows. Has shipped customer-facing React/TypeScript experiences driven by Optimizely experimentation and built reliable partner-facing microservices/SDKs on AWS, including resolving production traffic loss caused by edge security (DataDome/CAPTCHA) conflicts with payment providers.”

“Full-stack engineer who built and owned an AI-assisted job-matching dashboard in Next.js App Router/TypeScript, keeping LLM logic server-side and improving performance via deduplication, caching/revalidation, and streaming (35% fewer duplicate LLM calls; 40% faster first render). Also has strong data/backend chops: designed Postgres models and optimized queries at million-record scale (1.8s to 120ms) and built durable AWS multi-region telemetry workflows with idempotency, retries, and monitoring.”

“Software engineer with experience at Striim and Amazon who ships end-to-end production systems across UI, backend, ML, and operations. Built a real-time PII detection capability for a streaming data platform by integrating Python ML inference into a Java monolith via gRPC sidecars, achieving ~3M events/hour throughput and ~93% accuracy, and helped drive enterprise adoption (Fiserv, CVS). Also modernized internal Amazon tooling for multi-region scale with modularization and fully automated deployments.”

“Backend/platform engineer with payroll domain depth who built high-volume payroll processing microservices (Java/Spring Boot, Kafka, PostgreSQL, Redis) on AWS Kubernetes and debugged major peak-cycle latency by redesigning transaction boundaries and moving to async Kafka processing (>50% latency reduction). Also shipped an LLM-powered HR assistant using RAG with strong security/guardrails (RBAC, PII masking, audit logs) that cut support tickets by 40%, and designed reliable multi-step agent workflows with retries, circuit breakers, and idempotency.”

“QA automation engineer with healthcare web experience who owned an end-to-end automated test suite (Java/Cucumber/Selenium and Cypress) and integrated it into CI/CD (Jenkins to GitHub Actions, qTest DoD gates). Known for boosting regression coverage to ~93%, stabilizing flaky Cypress tests, and catching production-impacting pipeline/environment redirect issues through workflow updates and cross-browser/regional scenario testing.”

“Full-stack engineer at Bank of America who built and iterated a real-time transaction monitoring/fraud detection system processing 50K+ daily transactions, improving latency (25%), dashboard performance (30%), and reducing manual investigation time (40%) while meeting PCI DSS via OAuth2 and RBAC. Also built a scalable ETL pipeline for messy financial data with strong reliability/observability (ELK, retries, DLQ), boosting data integrity from 87% to 99% and sustaining 99.8% uptime.”

“Application-focused software engineer with experience at Amazon and Motorola shipping production systems ranging from developer monitoring/on-call tooling (Alcazar, ~40% MTTR improvement) to consumer AI features used by 100K+ users. Currently building an AI/ML-driven platform with a Python/FastAPI backend on AWS (ECS/RDS/S3) and has handled real production latency/scaling incidents end-to-end.”

“Backend/platform engineer with experience across edtech, logistics, and AWS internal systems—owned a production course recommender end-to-end (model serving + APIs + caching/observability), delivering +30% CTR and -20% latency. Has scaled real-time delivery visibility/rerouting on Kubernetes/EKS to sub-200ms P95 during demand spikes and built billion-events/day telemetry pipelines on AWS (Kinesis Firehose, Lambda, S3, Redshift) with schema evolution, dedupe, and replay support.”

“Backend/LLM engineer who built a production-critical Amazon Bedrock + RAG correction and compliance layer for employee communications, integrating tightly with existing Spring Boot/AWS microservices to reduce manual review while keeping outputs explainable and auditable. Also designed an event-driven system processing 10M+ events/day (SQS/Lambda/DynamoDB/Elasticsearch) and handled on-call incidents with strong observability and reliability patterns (idempotency, retries, hotspot mitigation).”

“Software engineer intern at Nutanix who independently shipped and maintained an internal smoke-test/failure-analysis dashboard, integrating failure data from multiple upstream systems (e.g., Jira, Jenkins, CircleCI) via REST APIs. Also has prior data-science experience building Postgres-based asset management analytics with automated reporting and indexing for faster time-series retrieval.”

“Undergraduate robotics researcher who built a crowd-aware motion planning system to navigate safely and efficiently through dynamic pedestrian environments, implementing the full pipeline in ROS (move_base, global planning, SLAM/localization) and validating via 2D crowd simulation. Also brings modern software delivery experience from web apps, including Docker/Kubernetes-based cloud deployment and CI/CD with automated testing.”

“Backend/data engineer with production experience building high-concurrency customer engagement platforms at KomBea on AWS (EKS + Lambda) using FastAPI/Django, PostgreSQL, Redis, and strong observability. Has modernized legacy batch systems into modular Python services with parallel-run parity validation and phased rollouts, and has delivered resilient AWS Glue ETL pipelines with schema evolution and data quality controls.”

“Frontend engineer who led Take-Two’s first direct-to-consumer e-commerce platform, setting up a React/Next.js monorepo with CI/CD and semantic releases. Built a centralized, SSR-based payment micro-frontend (iframe + postMessage) integrating providers like PayPal/Braintree and Xsolla while meeting legal constraints around sensitive data, and drove measurable performance gains (~40% faster loads) through SSR and multi-layer caching (including Redis).”

“Amazon engineer who owned customer-facing Alexa features and built automation-heavy delivery practices (API/service-level testing in CI/CD) to ship quickly without sacrificing stability. Also built an internal self-service feature management/beta access platform (Angular + Spring Boot + event publishing) that replaced a multi-team ticket workflow with instant, auditable operations, and has deep microservices/Kafka experience with strong observability and reliability patterns.”