Vetted Amazon DynamoDB Professionals

Khoa Nguyen

Screened

Junior Software Engineer specializing in Python, AWS, and data/ETL systems

Washington, USA1y exp

“Data/ETL-focused engineer with Amazon experience building and deploying AWS-based pipelines that became the primary source of automated customer feedback insights (processing millions of records daily). Demonstrated strong incident troubleshooting across software/host/network layers using CloudWatch, traces, and metrics, plus hands-on stakeholder and on-site operator collaboration to translate reporting needs into star-schema data models and tailored Python ETL logic.”

Sachin Reddy Kunta

Screened

Mid-Level Backend Software Engineer specializing in payments, fraud systems, and AI agent infrastructure

San Francisco, CA3y exp

“Early-career engineer who owned an end-to-end objective assessment/coding contest platform at an edtech startup, using Postgres + S3 and Redis (queues + ZSET) to decouple and scale code submission processing with worker sandboxes. Also implemented idempotency controls and set up monitoring and CI/CD while the rest of the team focused on curriculum.”

Eduardo Diaz

Screened

Senior Full-Stack Software Engineer specializing in Python, FastAPI/Django, and Azure

Remote13y exp

“Backend/data engineer with production experience building real-time IoT telemetry pipelines for wind/solar assets at Siemens (FastAPI on Azure Event Hubs/Service Bus, Cosmos DB + SQL Server) and deploying GPS/fleet telematics microservices on AWS ECS Fargate with Terraform and blue/green CI/CD. Demonstrated strong reliability and performance chops, including a 30s-to-<100ms SQL optimization and owning a Kafka pipeline incident resolved in ~20 minutes.”

Sanat Ahuja

Screened

Senior Engineering Manager specializing in platform, data/ML, and identity/access systems

Los Angeles, CA16y exp

“Senior engineering leader from Goodyear’s AndGo startup-like division who scaled the org from 12 to 30+ across pod-based teams and introduced an Architect Guild/ARD governance model. Led a 4-month Europe launch requiring AWS regional infrastructure, GDPR compliance, i18n/l10n, and new EMEA reporting pipelines, and has hands-on depth in API performance, incident response, and GraphQL/Hasura adoption to boost product velocity.”

Mathew Martin

Screened

Mid-level Software Engineer specializing in cloud data platforms and LLM applications

New York, USA4y exp

“LLM/agent builder with experience shipping production LLM features at an early-stage ed-tech mental wellness startup (conversation analysis + structured feedback via FastAPI, OpenAI API, Render, CI/CD). Also built a multi-step dining concierge agent using OpenSearch over Yelp data with fallback query relaxation, and has enterprise data engineering experience at Capgemini migrating databases to Snowflake with robust ETL normalization and data-quality handling.”

Adam Safran

Screened

Engineering Director specializing in platform modernization, microservices, and cloud reliability

Pleasant Hill, CA26y exp

“Former founder (ran a custom web development shop in Los Angeles) with extensive startup experience and a solid working understanding of the VC ecosystem. Helped build and scale a team at Turo from founding member to ~10 people, and is motivated by ownership, impact, and originating ideas—interested in the venture studio model and disciplined about rapid validation and execution.”

Vamsi Reddy

Screened

Mid-level AI/ML Engineer specializing in healthcare and financial ML systems

Nashville, TN5y exp

“ML/AI engineer with hands-on experience shipping both predictive healthcare models and clinical GenAI assistants into production. They combine strong MLOps depth across Azure and AWS with healthcare-specific safety thinking, including PHI guardrails, retrieval grounding, and production monitoring, and they also built internal Python tooling for fraud ML workflows at Capital One.”

“Currently at Berryble AI, this candidate is building an LLM-based real-time interview analysis engine using FastAPI, WebSockets, fine-tuned models, and GCP/Cloud Run. They stand out for using AI and agent workflows pragmatically to accelerate development while keeping human ownership over architecture, security, reliability, and maintainability, and they are also pursuing a master's in applied machine learning.”

“Built and shipped a production LLM feature that converts natural-language search requests into Lucene queries for OpenSearch-backed device event data, improving usability for non-technical users. Brings hands-on experience across the full stack of agentic systems: model training, FastAPI/React integration, Kubernetes deployment on AWS, event-driven orchestration with NATS/Kafka, and production-grade evaluation/observability.”

“Hands-on engineering leader who has scaled teams quickly (hired 20 engineers in 4 months) and led major architecture shifts including monolith-to-microservices and serverless, async AI-driven medical data ingestion/search. Also drove a versioned-inventory redesign with auditability and rollback that reduced operational errors by 22%, and demonstrates strong incident response with clear stakeholder communication.”

“Software engineer with experience at Coinbase and Gol Airlines, leading full-stack and backend-heavy systems in high-scale, high-compliance environments. Stands out for owning ambiguous projects end to end, improving internal support workflows with measurable impact, and designing reliable integrations for both customer-facing and government-critical systems.”

Vasudev Konde

Screened

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

Phoenix, AZ5y exp

“AI/LLM engineer who has shipped a production document-intelligence agent that automated internal support workflows using RAG, tool calling, and robust fallback controls. Stands out for combining hands-on architecture with measurable business impact: 85% faster query resolution, 35% lower LLM cost, 40% fewer LLM calls, and enough automation to avoid adding 2-3 support engineers.”

“Banking infrastructure engineer who owns large-scale IBM Power/AIX (AIX 7.x, VIOS, HMC/vHMC) environments with hundreds of LPARs and deep PowerHA/SAN recovery experience. Also builds modern cloud delivery platforms—Azure DevOps/Jenkins CI/CD and Terraform for AWS/Azure (EKS/AKS, networking, security)—bridging legacy mission-critical systems and cloud-native automation.”

Aaron Mcanerney

Screened

Mid-level Backend Software Engineer specializing in data platforms and reporting

Pleasanton, CA5y exp

“Built a production Medicare Q&A chatbot using OCR (pytesseract), LangChain chunking, ChromaDB embeddings/retrieval, and an Ollama LLM. Thinks in terms of practical tradeoffs (cost, model selection, static vs frequently-updated corpora) and emphasizes deterministic testing plus observability for reliable LLM workflows; also has experience automating non-technical teams' pain points (e.g., recruiting event integration).”

“Builder/technical leader who was brought into Finicity to turn a credit-improvement concept into a viable product—architected, staffed, and launched what became Experian Boost. Delivered a major North American product launch in ~6 months, scaling to ~50,000 new users per day at launch and solving complex ML classification and distributed processing/order-of-operations challenges on AWS.”

“Full-stack engineer focused on high-throughput document/financial data platforms, building Angular/React front ends and Spring Boot microservices with Python/Flask services for heavy processing. Experienced in designing non-blocking, asynchronous workflows (Celery/RabbitMQ) and deploying containerized systems to AWS ECS with auto-scaling and CloudWatch monitoring.”

“CTO/AI executive with repeated 0-to-1 leadership and founder experience across banking software, cloud, and fintech. Most recently, as a fractional CAIO, built a 50+ person team and launched 3 products in 9 months generating $10M+ new revenue; previously founded Trilogy (200+ clients in 7 countries) and created cloud tech that helped drive a $35M acquisition by VMware.”