Vetted TypeScript Professionals

“Front-end engineer who built a sophisticated browser-based registration platform for the JPMorgan Corporate Challenge, serving global users and handling team-based registration complexity, concurrency, and performance. Stands out for combining React/TypeScript UI engineering with accessibility improvements, UX polish, and production-minded reliability practices like Datadog monitoring and Kubernetes health checks.”

“Built and deployed LLM-powered agentic systems including a multi-agent travel planning assistant using LangChain, RAG (FAISS), real-time APIs, and a supervisor agent to manage coordination and reduce hallucinations. Also developed a Text-to-SQL system with schema-aware validation guardrails, and collaborated with drilling domain experts at CNPC USA to build an ML model predicting rate of penetration (ROP).”

Nithyashree Raghunathan

Screened

Mid-level Full-Stack AI Engineer specializing in agentic systems

Santa Clara, CA5y exp

“QA/data pipeline engineer with hands-on AI product building experience, spanning enterprise AWS migration testing for Belgium postal services and personal multi-agent systems in fintech and recruiting. Stands out for combining rigorous validation and production stability work with modern LLM orchestration, guardrails, and messy-document normalization workflows.”

“Full-stack product engineer who has built both operational systems and enterprise AI copilots in production. They owned an AI-powered inventory platform end-to-end, driving a 45% drop in stock issues, and also shipped a Microsoft Teams-based HR/IT copilot using RAG and workflow automation that reduced repetitive support queries by roughly 30%.”

“Product leader with experience rebuilding teams and platforms in both healthcare and AI-enabled SaaS environments. Most notably rebuilt Uniform Teeth’s product organization, EMR, and patient app after a restructuring, contributing to major clinical efficiency gains and the company’s acquisition by Impress in 2022. Brings a strong human-in-the-loop AI philosophy, plus experience leading PMs, design, and engineering through high-change environments.”

“Built and owned Citigroup's ASTRA AI-powered test case generation platform end to end, from full-stack product experience to multi-agent LLM orchestration and RAG infrastructure. Drove test coverage from 40% to 95%, cut generation time from hours to minutes, and scaled the feature to 300+ daily users across 32 enterprise projects with sponsorship from Citi's CIO and Head of Engineering Excellence.”

“Built an internal AI-powered document search and Q&A platform at BNY that let employees query company documents in natural language and get grounded answers in seconds. Brings practical full-stack and LLM systems experience across React/TypeScript, FastAPI, Pinecone, OpenAI, and Claude, with clear emphasis on retrieval quality, hallucination reduction, and production monitoring.”

“Platform/DevSecOps engineer who combines full-stack product ownership with practical LLM systems in production. They built a self-service secrets management portal that reduced DevOps bottlenecks while maintaining compliance, and shipped AI-powered deployment debugging and security-remediation workflows with strong guardrails, monitoring, and human-in-the-loop controls.”

rajasri mamidi

Screened

Mid-level Frontend Engineer specializing in FinTech web applications

Jersey City, NJ5y exp

“Frontend-leaning product engineer with strong end-to-end ownership across AI support and real-time observability products. They combine React/TypeScript architecture depth with backend/API collaboration, deployment ownership, and measurable impact, including a 40% reduction in support-agent lookup time.”

“Built and owned an AI-powered real-time financial fraud detection and monitoring platform end-to-end, spanning product decisions, backend architecture, frontend dashboards, deployment, and production support. Their work scaled to 120M transactions/day and materially improved fraud detection accuracy from 78% to 94%, showing rare breadth across distributed systems, observability, and React-based operational analytics.”

Murali Marupudi

Screened

Mid-level Backend Engineer specializing in Python microservices and scalable systems

Jersey City, NJ4y exp

“Full-stack engineer with hands-on experience shipping both secure platform features and production AI systems. They combine React/TypeScript, Flask/Node.js, and PostgreSQL fundamentals with practical LLM and NLP implementation, including retrieval, schema-validated outputs, monitoring, and human-in-the-loop safeguards. Notable impact includes cutting manual review by 40% and reducing post-update error rates by over 20%.”

PrabhjyotKaur Bamrah

Screened

Mid-level Full-Stack Software Engineer specializing in enterprise apps and AI integration

Redwood City, CA4y exp

“Engineer with experience scaling enterprise AI products in production, including a C3 AI deployment expanded from 2 to 4 sites across the US and Canada. Also built a GPT-4o-powered RAG assistant for plant operators, combining structured and unstructured data with human-in-the-loop safeguards and iterative evals to improve answer quality.”

“Frontend-leaning full-stack developer with hands-on experience building a proof-of-concept customer service application at Florida Blue using React/Redux Saga, Node/Express, and MongoDB. Also contributed at Yahoo via Wipro on a metrics dashboard, where their UI changes became the basis for additional team features.”

“Backend engineer focused on Java/Spring Boot microservices, workforce scheduling APIs, and event-driven systems. He uses AI tools pragmatically—roughly 25-30% assistance for scaffolding and optimization—while keeping architecture, debugging, testing, and final decisions under tight manual control. Strong on reliability and observability, with hands-on experience in Kafka-based workflows, distributed tracing, and evaluating agent frameworks like LangChain against production needs.”

“Backend engineer who designed and evolved an AWS-based event-processing system in Python/PostgreSQL, achieving a 60% p95 latency reduction while improving reliability during traffic spikes. Led a zero-downtime migration from a monolithic Django app to FastAPI microservices using feature flags, strong testing, and cross-team coordination, with production-grade observability (Prometheus/Grafana/CloudWatch) and security (JWT/OAuth2, RBAC, Postgres RLS).”

“Backend engineer who built an async FastAPI data pipeline at GHN Career Academy to replace a manual Excel-based workflow, migrating 30k+ contact records into Airtable with validation/deduplication and best-effort GPT-based enrichment. Emphasizes reliability under messy real-world data and partial failures via structured logging, retries, and resumable processing, unlocking downstream automations (e.g., Zapier and chatbots).”

“Backend/data engineer who builds production FastAPI microservices and AWS serverless/Glue pipelines for SMS analytics and marketing segmentation. Led a legacy batch modernization into modular services (FastAPI + Glue/Athena + ClickHouse) using shadow-mode parity checks, feature flags, and incremental rollout. Demonstrated measurable performance wins (12s to sub-second SQL; ~40% CPU reduction) and strong incident ownership with proactive schema-drift prevention.”

“Candidate indicated they live in New York but did not provide substantive details about their experience; they declined to discuss at least one topic as restricted and did not answer role-related questions with concrete examples.”

“Frontend engineer with hands-on experience leading architecture and quality practices across Angular and React/TypeScript products, including dynamic UI generation driven by backend configuration. Strong in building reusable design systems/component libraries and enforcing quality at scale via CI/CD SonarQube gates and comprehensive unit testing, with close collaboration alongside UX teams using Figma.”

“Built a web-based online Sudoku game in JavaScript (multiplayer format supporting up to 6 teams with up to 5 players each) and demonstrates strong product/analytics orientation. Uses a KPI-driven approach (DAU/WAU, ARPU, session duration, LTV) and structured prioritization methods (MoSCoW, story mapping, cost of delay, DFV) to iterate toward targets; seeking a remote role around $70k/year.”

“Backend engineer who has built high-throughput analytics and fraud-detection systems, combining Python/Flask + Celery/RabbitMQ with strong PostgreSQL performance tuning (indexing, partitioning, EXPLAIN ANALYZE). Has production experience integrating ML inference (scikit-learn/TensorFlow → TensorFlow Lite) into Spring Boot microservices with caching and model versioning, plus designing secure multi-tenant architectures using JWT-based tenant routing and PostgreSQL RBAC/RLS.”

“Master’s-in-Data-Science candidate (UHV) with 4+ years in AI engineering building production LLM and multimodal systems. Designed an LLM-powered workflow automation platform using RAG over vector stores with guardrails (schema/output validation, fallbacks) and a rigorous evaluation/monitoring framework including drift tracking and shadow deployments. Experienced orchestrating large-scale vision-language pipelines with Airflow and Kubernetes (OCR, distributed training) and partnering with non-technical ops stakeholders to cut cycle time and reduce errors.”

“Backend/platform engineer who owned a real-time customer analytics microservice stack in Python/FastAPI with Kafka streaming into PostgreSQL, including schema enforcement (Avro) and high-throughput optimizations. Strong Kubernetes + GitOps practitioner (EKS/GKE, Helm, Argo CD) who has handled CI/CD reliability issues with automated pre-deploy checks and rollbacks, and supported major migrations (on-prem to AWS; VM to EKS) with blue-green cutover planning.”

“Backend engineer with hands-on manufacturing/production-systems experience at Wallbox, improving the Supernova charger rework process by streamlining part-number/component updates. Strong in building modular Python/Flask services with clean integration layers (Cosmos DB, NetSuite, traceability/label printing), plus deep SQLAlchemy/Postgres performance tuning. Also brings scalable AI/ML integration and deployment experience (OpenAI/Hugging Face/TensorFlow Serving, Docker/FastAPI/Nginx) and multi-tenant schema isolation with RBAC.”