Vetted Amazon S3 Professionals

“Backend/platform engineer from Fanatics sportsbook core team with deep experience in real-time ingestion systems (Kafka) and high-throughput performance optimization. Delivered an 87% latency reduction on a Java API handling hundreds of thousands of updates per second, and improved reliability of shared internal libraries via deterministic recovery logic, strong testing, and feature-flagged rollouts.”

“Founding engineer for an AI product (“world’s first funny AI”) who designed and implemented the full-stack architecture (React/TypeScript + Node) and migrated production from Vercel to AWS. Shipped a Lambda-based image pipeline that eliminated lag/missing images and brought page load times to under a second, and has hands-on experience integrating multiple LLM providers (OpenAI, Claude, Gemini, Grok) with structured-output and self-check reliability techniques.”

“Backend engineer who has led major platform evolution to cloud-native microservices (Spring Boot on AWS with Terraform) and built scalable, secure FastAPI APIs. Demonstrates strong production rigor with metric-driven validation, canary/phased rollouts, and incremental migrations using shadow traffic/feature flags/parallel writes—achieving faster deployments, fewer incidents, and zero-downtime traffic spikes and migrations.”

“QA automation engineer with experience at Amazon Game Studios owning an end-to-end automated scale testing suite that simulates high-concurrency gameplay and captures performance telemetry. Improved coverage by bypassing hours of gameplay via programmatic state setup, enabling repeatable 4000-player dungeon-entry tests that exposed a messaging-queue bottleneck fixed before release. Also built maintainable Selenium/pytest UI automation with CI gating, reporting, and flake-reduction patterns.”

“Engineering leader/player-coach who led a high-stakes 0→1 in-house usage-based billing/rating platform to replace a third-party system, saving millions and protecting 30M+ in revenue. Deep experience in event-driven microservices on AWS (Lambda/SQS/DynamoDB), billing correctness, migrations, and incident response, while scaling teams through hiring, coaching, and lightweight execution processes.”

“Software engineer in the mortgage/financial services domain (Freddie Mac) who builds end-to-end loan origination and credit risk capabilities using Spring Boot microservices, Angular dashboards, and data pipelines. Delivered measurable impact (30% reduction in underwriting turnaround time) and emphasizes production reliability/compliance with strong guardrails, observability, and evaluation loops for risk scoring systems.”

“Uber engineer who has owned internal products end-to-end across backend (Spring Boot microservices, MySQL) and frontend (React), including performance optimization and secure JWT-based auth. Also shipped a production internal RAG/embeddings LLM support assistant over policy docs and support tickets, with guardrails (confidence thresholds, human review) and an evaluation loop that directly reduced hallucinations.”

“Early-stage founder building an engineering alpha product and planning a structured path to pilot and general availability. Active mentor in TechStars and MassChallenge with a strong VC network, emphasizing PMF, MVP-in-market feedback, and early sales while maintaining a sustainable approach to entrepreneurship.”

“Built and shipped a production LLM-powered healthcare support agent at UnitedHealthGroup, using LangChain + FAISS RAG on AWS SageMaker with CloudWatch monitoring and human-in-the-loop fallbacks for safety. Strong focus on reliability engineering (confidence gating, retries/timeouts, caching) and continuous evaluation loops; reported ~40% improvement in query resolution efficiency while reducing manual support workload.”

“Data engineering-focused candidate (internship/project experience) who built end-to-end pipelines processing a few million transactional records/day for fraud detection and reporting, using Airflow, Python/SQL, and PySpark with strong emphasis on data quality gates, idempotency, and monitoring. Also implemented an external web/API data collection system with anti-bot tactics and schema-change quarantine, and shipped a versioned Flask API to serve curated warehouse data.”

“Senior software engineer (5+ years) from Walmart Global Tech who owned and operated high-scale supplier inventory submission systems, including a microservice handling submissions up to 500k items and a data platform processing ~10TB/day. Strong in AWS/Kubernetes (EKS), Kafka/Spark streaming + batch pipelines, and production operations (on-call, metrics/alerting), with demonstrated performance wins (30% faster responses, 50% faster processing).”

Allan Farinas

Screened

Senior Full-Stack Software Engineer specializing in Python and AWS

West Covina, CA11y exp

“Backend/data engineer who has built production Python microservices (FastAPI) and AWS-native platforms for event ingestion and analytics, combining ECS/Fargate + Lambda with CloudFormation-driven environments and strong secrets/IAM practices. Experienced modernizing legacy logic with parallel-run parity validation and safe phased cutovers, and has demonstrated measurable SQL tuning wins (20–30s down to 1–2s) plus incident ownership in Glue/Step Functions ETL pipelines.”

Ethan Lam

Screened

Junior Software Engineer specializing in data platforms and full-stack development

Toronto, Ontario3y exp

“Software engineer with Warner Music Group experience owning and shipping analyst-facing data products (marketing/streaming data dashboards) end-to-end with high adoption through continuous stakeholder feedback. Also builds side projects with TypeScript/React and domain-driven API design, emphasizing flexibility (including swapping databases mid-development) and pragmatic microservices reliability patterns (logging, timeouts, retry backoff).”

Pooja Dokuri

Screened

Mid-level AI/ML Engineer specializing in GenAI, RAG pipelines, and cloud MLOps

Remote, USA4y exp

“Built and deployed a production LLM + vector search clinical decision support system at UnitedHealth Group, retrieving medical evidence and patient context in real time for prior authorization and risk scoring. Strong in end-to-end RAG architecture (Hugging Face embeddings, Pinecone/FAISS, SageMaker, Redis) plus orchestration (Airflow/Kubeflow) and rigorous evaluation/monitoring, with demonstrated ability to align solutions with clinical operations stakeholders.”

Evan Z

Screened

Junior Software Engineer specializing in video streaming and processing systems

Champaign, IL1y exp

“Software engineering intern at China Telecom who built and continuously evolved a real-time transaction platform ("Smart Tangerine") focused on strong consistency and peak-hour concurrency. Implemented microservices with Redis and RabbitMQ to decouple heavy processing and cut latency (~80ms to ~30ms), and led a zero-downtime migration from a monolith using strangler pattern, dual-write, and traffic shadowing.”

SaiTeasmitha Kaja

Screened

Mid-level Full-Stack Software Engineer specializing in Java/Spring Boot and cloud microservices

Houston, TX4y exp

“Backend-focused Python/Flask engineer who has built authentication/profile services with clean modular architecture (blueprints + service layer) and tuned SQLAlchemy/Postgres for scale using indexing, query rewrites, and pagination. Has production-style integration experience for AI/ML via TensorFlow Serving and OpenAI APIs (batching, rate limiting, caching), plus multi-tenant data isolation and high-throughput background processing with Celery/Redis and idempotent jobs.”

Ganesh Bandi

Screened

Mid-level AI Engineer specializing in LLMs, RAG, and MLOps

USA6y exp

“LLM engineer who has deployed production RAG systems for regulated document QA (PDFs/knowledge bases), emphasizing grounded answers with citations, RBAC, monitoring, and continuous feedback. Demonstrates deep practical expertise in retrieval quality (semantic chunking, hybrid BM25+embeddings, re-ranking), reliability (guardrails, deterministic workflows), and measurable evaluation (golden sets, log replay, A/B tests) while partnering closely with compliance/operations stakeholders.”

Satwik Alla

Screened

Mid-level Full-Stack Software Engineer specializing in scalable APIs and real-time AI apps

United States of America3y exp

“Lead software engineer (3+ years) who built and scaled an AI product backend at Cosmo AGI from the ground up using FastAPI/Postgres/Redis/vector DB, targeting sub-200ms latency and supporting 1000+ active users. Strong in production-grade security and observability (OAuth/JWT, RBAC, Postgres RLS, Prometheus/Sentry), plus DevOps automation (Docker, GitHub Actions, blue-green deploys) with measurable impact on uptime, incidents, engagement, and deployment speed.”

John Hoffman

Screened

Senior Data Engineer specializing in Databricks, Spark, and AWS for government healthcare data systems

Windsor Mill, MD12y exp

“Python/AWS engineer focused on batch-processing and data workflows, including building reusable S3/boto3 utilities with reliability features and IAM-based auth. Has led low-risk legacy modernizations using parity testing plus a month of parallel production runs, and has owned production issues end-to-end (including fixing a client-side Excel macro) while contributing to significant AWS cost reductions (~$10k/month).”

Sai Charan Kolla

Screened

Mid-level AI/ML Engineer specializing in LLMs, RAG, and MLOps on AWS

TX, USA5y exp

“LLM engineer who built a production document intelligence/RAG pipeline to extract structured data from thousands of unstructured PDFs, cutting manual review time by 60%. Experienced with LangChain and Airflow orchestration plus rigorous evaluation (labeled datasets, prompt testing, HITL review, monitoring) to improve accuracy and reduce hallucinations while partnering closely with non-technical operations stakeholders.”

Samatha Amsala

Screened

Mid-level Data Engineer specializing in cloud data warehousing and analytics

Omaha, NE6y exp

“Data engineer at American Express who owned end-to-end pipelines for transaction and customer data used in finance reporting and risk analytics, processing ~5–8M records/day. Built Airflow-orchestrated ingestion (including external APIs/web sources) with strong data quality controls, monitoring/alerts, and resilient backfill/retry patterns, and also shipped a versioned REST API serving aggregated metrics to analytics teams.”

“Built and shipped a production-grade agentic RAG system at CVS Health for patient adherence and medication recommendations, processing 20k+ patient records/day. Strong focus on real-world reliability: hybrid retrieval tuned with re-ranking (<400ms latency), strict JSON/schema validation and tool guardrails, and monitoring/drift detection that reduced MTTD from 6 days to 18 hours while improving recommendation accuracy (+8%) and cutting escalations (~23%).”

Nirmal Attarde

Screened

Mid-Level Software Development Engineer specializing in backend microservices and cloud

3y exp

“Software engineer with Oracle experience deploying a BioCatch fraud-detection integration into HDFC Bank’s core banking platform, using phased rollout and real-time monitoring and reporting ~80% fraud reduction. Also built a modular speech-to-text product (VocalSense AI) achieving ~95% accuracy and has strong production incident response skills (15-minute recovery) plus AWS serverless API hardening for messy inputs.”