Vetted MySQL Professionals

Nicholas Kim

Screened

Entry-Level Software Engineer specializing in full-stack and backend development

Houston, TX0y exp

“Full-stack developer who built a workout tracker feature end-to-end on the PERN stack (Postgres/Express/React), including relational schema design, REST APIs, and optimistic UI updates. Also has Next.js App Router experience (dynamic routes, SSG/React Server Components) and a strong quality mindset from Boston Scientific, where they used TDD to support clinically sound ECG analysis software and drove backend test coverage to 97%.”

Sai Erramada

Screened

Mid-level Full-Stack Java Developer specializing in microservices and cloud-native systems

Wisconsin, USA6y exp

“Backend engineer with hands-on experience building real-time, event-driven systems at Walgreens, including a Kafka-based prescription status notification service and scalable pipelines for messy prescription/inventory data. Strong focus on reliability patterns (retries, idempotency, DLQs) and iterating based on pharmacist feedback to improve usability.”

Phanideep P

Screened

Senior Data Engineer specializing in cloud lakehouse and streaming data platforms

5y exp

“Data platform/data engineer with cross-industry experience in banking and healthcare, building cloud-native lakehouse architectures across AWS/Azure/GCP. Has owned high-volume (millions of records; TB/day) pipelines with strong data quality automation (dbt/Great Expectations), observability (Grafana/Prometheus), and real-time streaming (Kafka/Spark) for fraud monitoring; also delivered an early-stage migration from SQL Server to BigQuery with 40% batch latency reduction.”

Sandipkumar Prajapati

Screened

Mid-Level Software Engineer specializing in full-stack systems and authentication

New York City, NY4y exp

“Full-stack engineer who led production modernization of a legacy, latency-sensitive application into a React + microservices platform, with heavy TypeScript backend work to improve reliability and maintainability. Has operated and scaled authentication/identity services in production, addressing peak-traffic latency spikes via database tuning and improved observability, and emphasizes idempotent, retry-safe workflow design.”

Aniruddha Chakravarty

Screened

Junior Software Engineer specializing in cloud infrastructure, observability, and full-stack systems

Remote2y exp

“Built and productionized a predictive maintenance system (predictEngineLife) estimating Remaining Useful Life for PW4000 turbofan engines from large-scale, noisy telemetry—emphasizing modular pipeline design, deterministic preprocessing, and strong observability/guardrails. Also has hands-on experience diagnosing multi-agent LLM customer-support workflows (schema/state issues, fallback paths, regression tests) and has led developer workshops (GDG Pune) while partnering with sales teams on technical discovery and POCs.”

Srinandh Reddy

Screened

Mid-Level Software Engineer specializing in backend, cloud, and event-driven systems

Aurora, Illinois5y exp

“Robotics software engineer focused on backend and distributed systems for real-time robot operations, including sensor ingestion, robot state management, and robot-to-cloud communication. Hands-on with ROS/ROS2 integration and real-time navigation debugging, plus production-grade monitoring, CI/CD, and containerized deployments (Docker/Kubernetes) to improve stability and performance.”

“Backend/data engineer focused on fintech payments and fraud systems, owning real-time Kafka-based reconciliation pipelines end-to-end (~13k tx/day). Built audit-friendly validation/reconciliation (SQL + Python), kept lag to seconds, and cut errors ~20%, while also shipping Spring Boot APIs with Redis caching and strong idempotency/versioning. Has early-stage startup experience standing up payment services on AWS with Docker + GitHub Actions and production monitoring/incident handling.”

“GCP-focused database/infrastructure engineer with hands-on production support for Cloud SQL and Firestore, spanning provisioning, IAM, scaling, backups, and performance tuning. They also described supporting a hybrid GCP architecture for a monolithic on-prem PostgreSQL workload and resolving a major latency incident by tracing cascading failures and fixing indexing issues.”

Rajeshwar Peri

Screened

Mid-level Data Analyst specializing in healthcare and financial analytics

Chicago, IL5y exp

“Healthcare analytics candidate with hands-on experience turning messy claims and CRM data into validated reporting tables, automating monthly reporting in Python/Airflow, and operationalizing churn metrics in SQL and Tableau. They appear especially strong in stakeholder-aligned metric design and delivered a reported ~10% churn reduction through cohort analysis, segmentation, and at-risk member targeting.”

“Built and shipped LLM-enabled decision systems focused on real production reliability rather than chatbot demos, including a multimodal radiology retrieval platform with 28% relevance gains and 35% lower latency. Also architected a 4-agent employee analytics workflow with structured outputs, traceable orchestration, and strong safeguards for messy real-world data.”

Scott Knight

Screened

Director-level software engineering leader specializing in SaaS and Healthcare IT

Portland, OR23y exp

“Candidate is exploring startup ideas focused on SaaS tools for small and medium-sized businesses, especially IT and HR automation. They have prior experience in VC-backed companies and with accelerators, and stand out for emphasizing real customer feedback and prototyping over echo-chamber startup advice.”

“Built and shipped a production LLM-powered email automation agent for procurement that ingests emails/attachments, classifies requests via rules+embeddings+LLM fallback, enriches responses with SAP inventory data, and generates templated replies. Architected it as an event-driven, idempotent Azure Functions/Queues pipeline with schema-constrained outputs, confidence gating, retries/circuit breakers, and Application Insights monitoring—cutting turnaround time from 4–7 days to near real-time while maintaining zero downtime.”

Kush Shah

Screened

Junior Full-Stack Software Engineer specializing in web apps and automation

Remote, USA3y exp

“Backend engineer with hands-on experience building an AI-powered document processing pipeline for insurance workflows from design through deployment and production support. They combine LLM-based extraction with rule-based validation, retries, and observability, showing a pragmatic approach to making AI systems reliable in high-stakes environments.”

“Frontend-leaning full-stack web developer who helped build an ecommerce SaaS platform from its early foundation, including reusable CMS widgets, client-specific theming, and later modernization efforts. Stands out for successfully navigating a legacy Backbone/Marionette ecosystem, helping introduce React, Storybook, and Jest, and for hands-on accessibility audit work that brought products toward VPAT and WCAG AA/AAA compliance.”

“ML/AI engineer with hands-on ownership of fraud detection and investigator-assist systems, combining anomaly detection with RAG-based LLM summarization in production. Stands out for translating research ideas into reliable cloud-deployed workflows that improved precision to 92%, cut review time by 25-30%, and increased investigator throughput by roughly 30% while also building reusable Python infrastructure for team-wide velocity.”

“Full-stack AI engineer who has owned production deployments for both a voice journaling/emotional insights app and a RAG-based research assistant. Stands out for turning messy, failure-prone LLM and document pipelines into reliable user-facing systems through strong debugging, staged workflow design, and post-launch stabilization.”

“Built production AI agents that convert natural-language requests into structured workflows using LangChain, tool calling, and a Kafka/Kubernetes backend, with strong emphasis on tracing, validation, and self-correcting failure handling. Also drove a zero-to-one Research Day judging platform spanning React, Flask, RAG, and ILP-based assignment optimization for ~100 live posters, achieving 99% uptime and winning Best Web App.”

Rohan Chodapunedi

Screened

Entry-level Data Scientist specializing in LLMs and analytics

Folsom, CA1y exp

“Built a zero-to-one AI contract/policy QA agent for compliance and data teams, with a strong emphasis on trust, traceability, and clause-level citations rather than just fluent answers. They combine full-stack product ownership with practical LLM systems design, including hybrid retrieval, structured outputs, and evaluation pipelines to improve reliability, latency, and cost.”

“Engineer with hands-on experience embedding AI into software delivery workflows, including Claude-powered PR review, testing, debugging, and multi-agent coding pipelines. They pair AI automation with strong systems thinking around microservices, fault tolerance, multi-AZ design, caching, and security controls like WAF and rate limiting, and also experiment independently with RAG and multi-agent search projects.”

Sakshi Patel

Screened

Mid-level Software Engineer specializing in e-commerce and supply chain platforms

Remote, USA3y exp

“AI-focused developer who has built several practical AI products, including EchoMate, a voice-agent system designed to act as a proxy for doctors and support patients when physicians are unavailable. Also has experience with multi-agent/API-based workflows in a solar suitability project, showing interest in applying AI across both healthcare and climate-related use cases.”

George Platon

Screened

Principal Full-Stack Engineer specializing in AI, DevOps, and cloud platforms

Romania, Romania16y exp

“Built a production end-to-end AI video-to-reels clip extraction system using a multi-agent architecture with transcription, captioning, effects generation, and centralized orchestration. Demonstrates unusually strong systems thinking around reliability, observability, evaluation, and production tradeoffs for LLM-powered workflows, including Kubernetes/Kafka-based deployment and regression-driven prompt governance.”

“Engineer with hands-on experience owning customer deployments for ordering and billing systems at Amdocs, including performance tuning, CI/CD improvements, and post-launch stabilization that delivered about 50% faster execution time. Also built and debugged an LLM-powered task prioritization app using Gemini, Streamlit, Python, and MongoDB, with a strong focus on prompt reliability, validation, and handling inconsistent real-world inputs.”

“Software engineer focused on backend/full-stack, distributed systems, cloud infrastructure, and AI-related work. Stands out for using AI and multi-agent workflows as an engineering accelerator while maintaining rigorous testing, logging, and system-level validation, including work on telemetry and monitoring platforms where reliability and correctness are critical.”

“Data engineering/software development candidate who built a stock market pipeline and uses that project to demonstrate strong architectural thinking across Kafka, Spark, and Airflow. They stand out for a pragmatic approach to AI: using tools like Copilot, ChatGPT, LangChain, and AutoGen to accelerate development while maintaining human oversight, testing, and system-level decision making.”