Vetted Software Developers

“Built and deployed a production chatbot on osvaldocalles.com and iterated through real-world LLM engineering issues: model quota/cost tradeoffs (migrating to Nova Pro), RAG accuracy via semantic chunking, AWS IAM/guardrail/security pitfalls, and Lambda/API Gateway streaming constraints (prefers JS for streaming layer). Experienced with agent orchestration using Strands SDK (AWS-focused) and LangGraph (Vercel/container deployments), plus evaluation pipelines using LLM-as-evaluator, dashboards, and staged model rollouts.”

“Early-career software engineer who owns revenue-critical invoice processing and internal ops tooling end-to-end. Has built TypeScript/React systems backed by MongoDB and Temporal, and designed scalable SQS-based onboarding workflows with FIFO/DLQ monitoring. Notably redesigned an Authzed SpiceDB authorization model, shrinking a 500+ line schema to ~20 lines while meeting sub-100ms p95 latency.”

“Customer-facing technical professional with Amazon incident-management experience who helps drive adoption of complex ML/LLM solutions by delivering hands-on demos and rapid model fine-tuning. Applies a disciplined debugging approach (repro + logs/metrics + severity triage) and maintains runbooks to resolve SEV2 issues in ~1 hour, while also partnering with sales/customer teams to ship patches and new features based on feedback.”

“Engineering leader with experience building point-of-care diagnostics platforms (IoT-connected PCR device delivering results in <15 minutes) and scaling multidisciplinary teams (55+). Has led major data/IoT architecture decisions (multi-cluster Kubernetes with secure routing; Kafka + Gobblin over MQTT) and runs execution with Agile roadmaps tightly aligned to GTM and senior leadership.”

“AI/LLM practitioner with internships at Dell Technologies and Roche who built and deployed a healthcare-focused "Doctor LLM" by fine-tuning Meta Llama 3.2 on healthcaremagic.json, emphasizing safety guardrails to prevent harmful medical advice. Experienced in productionizing AI workflows with monitoring, testing, and orchestration (Airflow, Kubernetes), and in delivering AI-agent-driven competitive landscape insights to non-technical business stakeholders.”

“Backend engineer who built gnocal, a ~150-line stateless Go service that turns on-chain event data into standards-compliant .ics calendar feeds consumable by Apple/Google Calendar, deployed on Fly.io. Also refactored MCTS into Monte Carlo Graph Search (Python-to-Rust) using deterministic tests and state canonicalization to handle transpositions, and implemented decentralized role-based ACLs in Gno for a smart-contract web hosting network (gno.land / All in Bits).”

“Backend/data engineer with experience building Kafka-driven real-time pipelines that support ML code deployment and downstream integrations. Currently migrating high-throughput mainframe (COBOL/assembly) processing to Java, using Spark/Databricks to preserve performance and employing rigorous A/B testing across dev/pre-prod/prod with years of historical data.”

“Backend/data engineer with production experience at Walmart and HealthSnap building Python services and data pipelines on AWS (EKS, Lambda, Glue, Airflow). Strong reliability and operations focus—implemented idempotency + circuit breakers for peak-traffic consistency issues, GitOps CI/CD, and observability. Demonstrated measurable performance wins (Postgres p95 45s to <5s, ~60% CPU reduction) and modernized SAS batch workflows to Python with parallel-run parity validation and feature-flagged rollout.”

“Backend/data engineer who has owned production Python APIs and high-throughput async workflows on AWS (FastAPI, Docker, ECS/EKS/Lambda) with mature reliability practices like idempotency, bounded retries, circuit breakers, and strong observability. Also built AWS Glue ETL into an S3/Redshift lakehouse and modernized legacy batch systems via parallel-run parity testing and feature-flagged migrations, including a SQL tuning win cutting a multi-minute query to under 10 seconds.”

“Backend-leaning engineer with experience at Dropbox, Wayfair, and Etsy who has led cross-product integrations and internal platform tooling. Re-architected a legacy promo code system from a PHP monolith to a Java/Spring Boot microservice achieving a 99% execution-time reduction, and built a React/TypeScript + Supabase product (press.social) with LLM-powered bulk parallel generation and a path to multi-tenancy.”

“Software engineer with 2.5 years at Amazon working on the Package Tracking page (Amazon’s most visited page), delivering new customer actions like Cancel Delivery and Buy Again within a Spring Boot-based stack. Has hands-on experience with feature-flagged rollouts (Weblab), A/B testing, and scaling/load testing for Prime Day-level traffic, and is upskilling into React while leveraging modern AI coding tools on side projects.”