Vetted SQLite Professionals

“Backend/platform engineer who owned an end-to-end financial data ingestion and validation system (Python/Django/FastAPI, Postgres, AWS), including large-file performance tuning, auditability, and CI/CD. Strong Kubernetes/EKS + ArgoCD GitOps practitioner and has delivered both Kafka-based real-time transaction streaming and a legacy on-prem stack migration to AWS (ECS Fargate, RDS, S3, Secrets Manager) with controlled cutovers and data consistency validation.”

“DevOps/GCP-focused engineer with experience helping move complex/LLM-style prototypes toward production by clarifying requirements, hardening architecture, and driving OS-level test remediation to full pass rates. Debugs LLM/agentic workflow issues like distributed systems using GCP observability (Cloud Logging/Monitoring, GKE metrics) and implements alerting policies for proactive communication. Has delivered internal DevOps training from basics through end-to-end GCP infrastructure and deployment, improving engagement with real-world examples and analogies.”

“Built a production AI-powered customer support Q&A system using an internal knowledge base to reduce repetitive ticket work and improve customer satisfaction, with an emphasis on source-backed answers and expert oversight. Also has experience defining deployment services in a microservices architecture and integrating large-scale APIs (including work connected to US HHS/COVID-19).”

“Backend/data engineer focused on production-grade Python services and AWS platforms: builds FastAPI microservices on EKS with strong reliability patterns, CI/CD, and observability. Also delivers AWS Glue/Redshift analytics pipelines with schema-evolution and data-quality safeguards, and has modernized legacy batch processing into maintainable services with parallel-run parity validation and feature-flagged rollouts.”

“Frontend engineer who has led mobile-first and web React/TypeScript products end-to-end, including an expense tracking app handling sensitive financial data and a real-time messaging/activity dashboard with chat, presence, and contextual side panels. Emphasizes scalable architecture, rigorous component-boundary testing, and production-safe rollout practices (feature flags, analytics/logging, staged releases) to ship reliably in fast-paced environments.”

“Built and shipped an AI-powered driver ranking/assignment system at AffirmoAI using LLM intent classification + RAG over pgvector/Postgres, served via FastAPI with a React UI that explains scores. Drove measurable improvements through optimization and iteration (latency down to <800ms, adoption 60%→90%+) and implemented rigorous eval loops with dispatcher ground truth plus cold-start handling for new drivers.”

“UE5 UI engineer who has shipped production-ready HUD/menu frameworks using C++/Slate/UMG and CommonUI, emphasizing MVVM-style architecture for maintainability and designer-friendly iteration. Strong in UI profiling/optimization (Unreal Insights + Slate Profiler), including Slate list virtualization and event-driven updates that improved UI frame time by ~30% in heavy menu scenarios.”

“Backend engineer working on Plumas Bank’s digital modernization, building a FastAPI-based loan origination/processing system with OAuth2/JWT security, AWS Lambda-driven PDF document generation to S3, and MongoDB integration. Has led a legacy workflow migration to a new microservice using dual-write/dual-read and monitoring, and emphasizes multi-tenant isolation via layered API controls plus row-level security.”

“Backend/data engineer who built a production-ready multi-agent financial intelligence system (Mycroft) that orchestrates specialized AI agents to analyze real-time market data using FastAPI and Pinecone vector search. Brings strong security/reliability instincts (rate limiting, JWT/OAuth2, retries/backoff, health checks) and has caught high-impact data integrity issues in financial migrations (timezone normalization across global legacy systems).”

“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).”