Vetted Amazon S3 Professionals

sai anuragh Sangoju

Screened

Mid-level AI/ML Engineer specializing in fraud detection, credit risk, and NLP

Dallas, Texas4y exp

“Built and deployed a production LLM-powered university support chatbot on Azure using a RAG pipeline, focusing on reducing hallucinations, improving latency, and handling ambiguous queries via confidence checks and clarification prompts. Also has hands-on orchestration experience (Airflow/Azure Data Factory), including hardening a demand-forecasting ingestion workflow with sensors, retries, and automated alerts, and uses a metrics-driven testing/monitoring approach for reliable AI agents.”

Mark Wlodawski

Screened

Senior Unity Developer specializing in AI/LLM systems and multiplayer VR

Orlando, FL11y exp

“Backend/data engineer focused on AWS-native Python systems: built a FastAPI microservice on ECS/Fargate serving real-time analytics at millions of daily requests with strong reliability (OAuth2/JWT, retries/timeouts, correlation IDs) and autoscaling. Also delivered Glue/PySpark ETL pipelines to curated S3 Parquet/Athena with schema evolution + data quality controls, owned Airflow pipeline incidents, and has a track record of measurable performance and cost optimizations (e.g., ~80%+ query latency reduction; reduced logging/NAT/Fargate spend).”

“Built and deployed a production LLM-powered RAG knowledge system to unify operational/policy information across PDFs, wikis, and databases, emphasizing auditability and low-latency/cost performance. Improved answer relevance at scale by moving from pure vector search to hybrid retrieval with metadata filtering and reranking, and partnered closely with healthcare operations/compliance to define acceptance criteria and human-in-the-loop guardrails.”

Susheel Thimlapur

Screened

Mid-level Full-Stack Engineer specializing in web applications and cloud systems

Bloomington, IN4y exp

“Software developer at Indiana University who built a phishing training platform using TypeScript/React, Node, GraphQL, and DynamoDB, including an admin tool to monitor student completion and send automated reminder emails. Also created TechRent, an IU-only electronics rental marketplace concept focused on improving security by restricting access to university students.”

Ruchi Desai

Screened

Senior Backend Engineer specializing in cloud-native .NET microservices

Frisco, TX8y exp

“Healthcare-focused full-stack engineer who has spent their career in small startup-like teams, owning products end-to-end from business requirements to architecture, implementation, deployment, and support. They’ve built critical hospital-facing systems including patient intake, insurance eligibility, appointment search at scale, and configurable multi-tenant admin platforms using React, Node.js, .NET, AWS, MySQL, and Elasticsearch.”

“New grad focused on AI systems and agent-based development, with hands-on experience using LLMs as a coding partner and building RAG-based document processing workflows. Stands out for practical experimentation with semantic chunking, retrieval optimization, and multi-agent architectures, including redesigning a RAG workflow by adding a reasoning agent to improve response accuracy and reliability.”

“QA automation engineer who owned an end-to-end, device-integrated mobile regression suite for Tandem’s insulin-pump-connected mobile app, covering pairing/connectivity/data sync and catching contract mismatches and firmware-related connectivity regressions. Strong in Cypress/JavaScript automation, CI gating in GitHub Actions, and diagnosing production-impacting sync issues using logs and API traces while influencing requirements early to improve testability and UX.”

“Candidate has hands-on experience at Cognizant building production-grade automation and integration solutions across Python ML services, Java microservices, Kafka, and Selenium-based UI testing. They stand out for a strong reliability mindset—covering failure modes, observability, flaky test hardening, and translating ambiguous payment-system business processes into resilient end-to-end automated workflows.”

“Healthcare-focused ML/AI engineer who has built production voice agents and clinical question-answering systems end-to-end, from experimentation through deployment, observability, and iteration. Particularly strong in making LLM systems reliable in real workflows via RAG, fine-tuning, guardrails, evaluation pipelines, and shared Python tooling; cites ~20% clinical QA accuracy gains and ~40% faster physician decision turnaround.”

“Full-stack engineer with payments/settlement domain experience who modernized a payment tracking workflow from REST to GraphQL and delivered a production payment status dashboard using Next.js App Router + TypeScript. Strong in performance and reliability work (Postgres indexing/Explain Analyze, Redis caching, Datadog observability) and in durable event-driven processing with Kafka (DLQs, idempotency, reconciliation, event replay).”

“Backend/data engineer with hands-on production experience across Python/Flask microservices and AWS serverless/data platforms (Lambda, DynamoDB, S3, Glue/PySpark). Demonstrated strong reliability and operations mindset (JWT/RBAC, retries/timeouts/circuit breakers, CloudWatch/SNS alerting) and measurable performance wins (SQL report runtime cut from 10 minutes to 30 seconds). Seeking ~$150k base and cannot travel for onsite meetings for the next 5–6 months due to family medical constraints.”

“Backend/data engineer with hands-on production experience building a real-time notification API on Flask/Celery/Postgres and scaling it on AWS with Docker, Redis queuing, and SQLAlchemy query optimization. Also delivered AWS serverless deployments (Lambda) using Terraform + GitHub Actions and built AWS Glue ETL pipelines from S3 to Redshift with CloudWatch monitoring and DataBrew data quality checks.”

Shrutika Chawla

Screened

Senior Full-Stack Developer specializing in React/React Native and SaaS platforms

Edmonton, AB7y exp

“Frontend engineer who has led end-to-end delivery of a climate-risk visualization/financial impact web platform using micro-frontends (Webpack Module Federation), a shared MUI design system, and React Query server-state to keep independent modules consistent and performant. Also improved a complex rules-heavy document editor (Crove.app) by eliminating input lag with memoization + Web Workers and introducing a headless rendering engine reused across products, with disciplined rollout via feature flags and Sentry monitoring.”

Xinyu Li

Screened

Junior Software Engineer specializing in backend systems and AI/LLM RAG platforms

San Jose, CA2y exp

“Full-stack engineer who built and operated a data-driven analytics platform using Next.js App Router/Server Components and TypeScript, owning post-launch monitoring and performance/stability work. Demonstrated measurable wins in analytics performance (e.g., cutting query latency from ~1s to ~200ms) through indexing, query-plan analysis, and precomputation/caching, and has experience designing durable multi-step backend workflows with retries, idempotency, DLQ, and time-correct ordering.”

“Application-focused software engineer working on AI-heavy products, with hands-on experience building end-to-end document processing, retrieval, and configurable workflow systems. Particularly strong in combining React/TypeScript UX, FastAPI/Postgres backend design, and LLM workflow reliability improvements through validation, prompt iteration, and reusable abstractions.”

Prudhvi Avula

Screened

Senior Full-Stack Software Engineer specializing in Java, React, and distributed systems

Austin, TX7y exp

“Implementation and AI workflow engineer who has owned customer deployments end-to-end for messaging/integration platforms and also built production-oriented LLM systems. Stands out for combining stakeholder-facing delivery leadership with hands-on experience in Kafka/MongoDB integrations, RAG/agent architectures, and resilient document-processing pipelines with strong validation and fallback controls.”

“Full-stack and AI engineer who has built both user-facing products and production LLM systems, including an AI log-classification and incident-triage platform that cut manual triage by 60%+ and improved routing accuracy by 35%. Also brings cross-functional systems experience from an AI-driven digital twin project spanning HPC, Unity, AR, and large-scale simulation visualization.”

“Robotics/embedded platform engineer who led compute provisioning and ROS2 platform development for a smart electrical panel, building a full ROS2 stack that bridges mobile app requests (via AWS IoT/MQTT) to signal-level CAN commands and returns telemetry/logs to the cloud. Demonstrated strong full-stack debugging by resolving flaky CAN traffic down to a custom PCB transceiver standby-pin grounding issue, and improved real-time behavior by refactoring middleware into C++ with timer-scheduled publishes to meet firmware watchdog expectations.”