Vetted Amazon VPC Professionals

Shriya Bannikop

Screened

Mid-level Software Engineer specializing in cloud platforms, data engineering, and distributed systems

Seattle, WA5y exp

“Full-stack engineer who built and owned an AI-assisted job-matching dashboard in Next.js App Router/TypeScript, keeping LLM logic server-side and improving performance via deduplication, caching/revalidation, and streaming (35% fewer duplicate LLM calls; 40% faster first render). Also has strong data/backend chops: designed Postgres models and optimized queries at million-record scale (1.8s to 120ms) and built durable AWS multi-region telemetry workflows with idempotency, retries, and monitoring.”

Bhanu Chander

Screened

Senior Data Engineer specializing in cloud data platforms and real-time pipelines

New York, NY6y exp

“Data engineer focused on reliability and observability, building end-to-end pipelines processing millions of records/day from sources like S3 and Kafka. Has hands-on experience with Airflow-based data quality automation, PySpark/Databricks transformations, and shipping versioned Python REST APIs deployed via Docker/Kubernetes with CI/CD (Jenkins) and monitoring (CloudWatch/Azure Logs).”

Nicholas Moore

Screened

Senior Full-Stack Engineer specializing in scalable cloud-native systems

Lehi, Utah13y exp

“Backend/data engineer with production experience building high-concurrency customer engagement platforms at KomBea on AWS (EKS + Lambda) using FastAPI/Django, PostgreSQL, Redis, and strong observability. Has modernized legacy batch systems into modular Python services with parallel-run parity validation and phased rollouts, and has delivered resilient AWS Glue ETL pipelines with schema evolution and data quality controls.”

Geetha Sri Kasu

Screened

Mid-level Software Engineer specializing in Java/Spring Boot, Kafka, and AWS

5y exp

“Software engineer who owned an end-to-end self-service reporting workflow (secure APIs, async/batched processing, and React UI), improving report generation performance by ~30–40% and reducing manual support effort. Also built a RAG/embeddings prototype over internal docs and service logs with grounding-focused guardrails, and has a strong reliability/observability mindset (retries, DLQs, CI/CD validation, dashboards/tracing) for distributed workflows.”

“Platform/infrastructure-focused engineer with hands-on experience automating AWS EKS upgrades in Python, building observability around logs/metrics/SLOs, and migrating Terraform delivery from CodePipeline to Atlantis. They describe shipping automation that handled 140 resources across 50+ Terraform files ahead of schedule and debugging a Karpenter/CoreDNS regression in Kubernetes by tracing it from regional traffic spikes to a missing local DNS cache configuration.”