Vetted Error Handling Professionals

“Full-stack engineer/product owner who built and scaled a customer-facing job application portal (Skillbridge) using TypeScript/React and Spring Boot/MongoDB, optimizing search performance with indexing, caching (Redis), and payload/lazy-loading improvements. Also built an internal AI-driven analytics dashboard for Salesforce operations using OpenAI sentiment analysis, achieving 70% reduction in manual analysis and driving adoption through demos and iterative feedback.”

“Full-stack engineer who built and owned an internal analytics dashboard for sales (React/TypeScript + Node/Express + NoSQL), delivering it two weeks early with zero production issues and a reported 10% sales-efficiency lift. Experienced with microservices and async messaging patterns (retries/DLQs/idempotency), and emphasizes rapid iteration with strong CI/CD and automated testing plus user-driven adoption.”

“LLM/agentic systems practitioner focused on taking customer prototypes to production by hardening reliability (APIs, monitoring, security) and adding guardrails, evals, and incremental rollouts. Experienced diagnosing RAG/agent failures via structured tracing and fixing retrieval-quality issues (freshness checks, filters, schema enforcement). Also supports pre-sales by leading developer demos/workshops and building targeted POCs to address scalability/reliability objections and drive adoption.”

“Robotics-focused engineer from a senior capstone who built the backend motion-control software for a semi-autonomous line-following vehicle split across two ESP32s. Experienced in ROS 2 (DDS, lifecycle nodes, QoS) and in bridging microcontroller telemetry to a laptop ROS 2 stack over UART with custom structured protocols, using Gazebo simulation to tune PID and validate behavior before deploying to hardware.”

“Customer-support/engineering background spanning Informatica PowerCenter ETL and IBM demos/workshops, with hands-on experience hardening data workflows for production (error tables/reject links, validation, restart strategies, alerting, performance tuning). Also demonstrates a clear, systems-level approach to diagnosing LLM/agentic workflow issues (prompt/RAG/tooling/memory) using instrumentation and iterative fixes, and has partnered with sales on POCs by defining success metrics and mapping solutions to customer architectures.”

“Backend engineer on Morgan Stanley’s trade risk and compliance platform, building Java/Spring Boot microservices that validate equity and fixed-income trades at multi-million-events/day scale. Shipped an LLM-assisted trade exception analysis feature using RAG over internal policy documents and trade history, with production-grade guardrails (confidence thresholds, audit logs, human-in-the-loop) and measurable performance wins (~30–35% faster reporting) through PostgreSQL tuning and Redis caching.”

“Deloitte engineer who built and shipped AI-powered, Kafka-driven workflow automation for transportation/document processing, including LLM-based semantic search. Strong in production reliability (idempotency, offset management, retries), observability (Datadog/CloudWatch), and database performance tuning (PostgreSQL/Flyway), with measurable latency improvements.”

“QA automation engineer who owned and transformed a JavaScript/WebdriverIO UI automation suite into a reliable CI release gate by refactoring to POM, adding API validations, cross-browser coverage, and aggressively reducing flakiness. Demonstrated strong security mindset by uncovering a critical RBAC gap where restricted users could trigger billing actions via direct API calls, and helped reshape product requirements early through detailed acceptance-criteria questions (e.g., CSV upload partial failures).”

“Software engineer with payments-domain experience (Visa) building real-time transaction monitoring and analytics systems. Strong end-to-end ownership across Spring Boot/Kafka microservices, PostgreSQL modeling, and AWS/Kubernetes operations, plus React+TypeScript dashboards—focused on low-latency processing, secure APIs, and zero-downtime production releases.”

“Full-stack engineer who built and supported production features in a productivity/task-tracking app using Next.js App Router + TypeScript (server components for initial render, client components for interactivity, API route handlers for mutations). Also designed and optimized Postgres data models/queries and implemented resilient, event-driven payment processing with idempotency, retries, audit logs, and strong testing/observability practices.”

“Software engineer with experience across TCS, Rakuten, and USC who has owned production integrations and data pipelines end-to-end. Notably improved a trading platform payment flow by replacing fragile polling with a webhook-driven status system with robust fallbacks, and has shipped LLM-assisted design-to-webpage automation plus evaluation-driven prompt iteration (NYT Connections).”

Sagar Patel

Screened

Mid-level Full-Stack Python Developer & Data Engineer specializing in ETL and web platforms

Arizona, United States6y exp

“Backend engineer who led major modernization efforts at GoDaddy, migrating legacy Perl services to Python/FastAPI with an incremental rollout strategy, containerization (Docker/Kubernetes), and CI/CD (Jenkins/GitHub Actions). Strong focus on secure, reliable API design (JWT, RBAC, PostgreSQL row-level security), rigorous testing, and data integrity—plus experience hardening an automated web-scraping pipeline against changing site structures and downtime.”

Fnu Pallavi Sharma

Screened

Intern Data Scientist specializing in ML, NLP, and MLOps for healthcare and enterprise AI

Madison, WI1y exp

“Built a production multi-cloud LLM-driven IT ticket automation system using LangGraph, Azure + Pinecone RAG, and an Ollama-hosted LLM on AWS, with Terraform-managed infra and PostgreSQL audit/state tracking for reliability. Also partnered with UW School of Medicine & Public Health students to deliver a glioma survival risk-ranking model, translating clinical feedback into practical pipeline improvements (imputation, site harmonization) and stakeholder-friendly visualizations.”

Gnaneswar Markat

Screened

Mid-level Software Engineer specializing in cloud-native distributed systems

Charlotte, NC4y exp

“Full-stack engineer with Bank of America experience building and owning a customer portfolio dashboard end-to-end, from requirements through launch and ongoing iteration. They combine React/Spring Boot/PostgreSQL implementation with strong performance tuning, real-time data handling, and UX improvements, and cite adoption by roughly 12,000 active internal users.”

“Enterprise-minded builder who has owned complex, high-impact systems from discovery through stabilization, including a customer master data platform at AB InBev serving 2,000 sales reps across 13 countries. Also demonstrates strong AI product instincts, having built a first-place ReAct-style NYC property intelligence agent at IBM's AI Demystified Hackathon, while showing deep rigor in data quality, integrations, and production reliability.”

Pavan Punna

Screened

Mid-level AI/ML Engineer specializing in LLMs, MLOps, and healthcare-fintech AI

Dallas, TX5y exp

“Built and owned a production GPT-4 RAG assistant for clinical and enterprise query resolution, taking it from initial experiment to deployment, monitoring, and iterative improvement. Their work cut resolution time from 45 minutes to under 2 minutes, achieved roughly 95% accuracy, and scaled to thousands of additional monthly queries while emphasizing safety and trust in a sensitive clinical domain.”

“JavaScript/React/TypeScript engineer with hands-on open-source experience improving a hooks utility library—fixed a reported async race condition that reduced unexpected re-renders and added a debounced callback hook that became widely used. Brings a production-minded approach to performance and abstractions (APM/metrics-driven, DB/caching focus) with strong testing, documentation, and community support practices.”

“Frontend-leaning full-stack engineer who built internal product capabilities at Mercedes-Benz R&D, including a vehicle exploration platform, test drive booking flow, and a 0→1 vehicle comparison feature. Stands out for combining strong React architecture and performance optimization with practical backend/API ownership in Node/Express and MongoDB.”

“Built Nexthire-AI, shipping an end-to-end LLM-powered resume–job description matching product (React + Node.js) using embeddings and retrieval to generate match scores and skill-gap recommendations. Improved post-launch engagement by making feedback cleaner and more actionable, and added production guardrails (validation, timeouts, fallbacks) to handle messy resume formats and AI API instability.”

“Engineer with a process-driven approach to AI-assisted software development, focused on orchestrating where AI adds value while maintaining human review and verification. Has applied this in backend work such as an S3-based invoice pipeline and used multi-agent workflows to speed up large API refactors across many endpoints.”

“Backend/platform engineer who has owned a Python/FastAPI results API and deployed it on Kubernetes with Helm and GitHub Actions-driven CI/CD. Demonstrates strong production operations mindset across performance tuning, monitoring, safe rollouts/rollbacks, and phased migrations, plus hands-on Kafka streaming experience focused on ordering and idempotency.”

“Entry-level software engineer with hands-on experience building a GPA predictor web app in a school project, focused on React/TypeScript frontend, authentication, and UX for AI-driven syllabus parsing. Stands out for translating ambiguous product ideas into a usable MVP, improving onboarding flow, and adding resilient loading/error states for unreliable parsing and API behavior.”

Aman Kushwaha

Screened

Senior Frontend Engineer specializing in React, Next.js, and FinTech UI architecture

Bangalore, India4y exp

“Frontend/product engineer with strong ownership across architecture, deployment, and cross-functional product decisions, especially in finance workflow systems. Built a metadata-driven React/TypeScript framework at Hyperbots that cut feature development effort by ~70% and manual effort by 50%+, and has also driven backend API cleanup, real-time experiences, and a full GA4 tracking architecture redesign.”

Yuanmu Li

Screened

Junior Software Engineer specializing in full-stack web applications

Sunnyvale, CA2y exp

“Full-stack product engineer in the health and wellness space who has owned prescription workflow features end to end, including React/TypeScript frontend work and GraphQL-backed API aggregation across messy downstream systems. Also shipped an internal OpenAI-powered support assistant with grounded context, structured outputs, validation, and human-in-the-loop safeguards—showing strong practical judgment at the intersection of healthcare workflows and applied AI.”