Vetted Asynchronous Processing Professionals

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.”

Yash Rangucha

Screened

Mid-level Software Engineer specializing in backend microservices and real-time streaming

Illinois, USA4y exp

“Built and owned an end-to-end LLM-powered enterprise retrieval pipeline at ServiceNow, spanning ingestion of structured/semi-structured sources through vector retrieval and real-time API serving. Focused heavily on reliability and quality (multi-stage validation, monitoring, evaluation pipelines) while also driving performance improvements (~35% faster responses) via caching, async processing, and SQL/query optimization.”

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.”

“Backend/ML engineer who built and operated a production WhatsApp assistant end-to-end using a modern RAG stack, delivering >90% automation with sub-2-second latency. Shows strong depth in retrieval quality, observability, evaluation, and incident handling, and has also applied similar AI workflow patterns to a clinical diagnostic assistant processing medical PDFs.”

“Built production-scale dashboards and real-time data systems across fintech and autonomous driving, with hands-on ownership from React frontend architecture through Python/Kafka/Elasticsearch backend pipelines. At Zoox, led development of an automated safety signal attribution platform that replaced manual engineering calculations and surfaced trends through dashboards.”