Vetted Idempotency Professionals

“Built and shipped an end-to-end LLM agent during an AT&T internship to automate network troubleshooting, with production-style reliability safeguards (timeouts/retries/fallbacks) and structured, state-machine orchestration; project won 3rd place in AT&T’s nationwide intern innovation challenge and was demoed to leadership. Also handled messy multi-partner data at Tencent by implementing schema validation/normalization, confidence-threshold fallbacks, and idempotent Python/ORM-based pipelines.”

“Built a production LLM-powered data ingestion workflow at Provi, an online alcohol marketplace, to clean and match millions of distributor inventory items against a product catalog. Their experience is strongest in applying LLMs to real-world, large-scale data operations with AWS Glue, S3, batching, API integration, human review, and drift detection.”

“Backend/data engineer with experience at AWS and Intuit building and operating production serverless systems and data pipelines. Delivered an internal AWS TV video-processing platform using Step Functions/Lambda/S3/DynamoDB with strong reliability and cost controls, and built Glue-based ETL for compliance/risk events (Kafka to partitioned Parquet). Also modernized legacy compliance systems into Java/Node event-driven services and has demonstrated measurable SQL tuning impact (200s to 20s).”

George Liu

Screened

Intern Software Engineer specializing in full-stack, backend, and AI agent systems

Fremont, CA1y exp

“Backend engineer with Tesla experience who redesigned vehicle registration into a step-based, region-configured workflow across 4–5 microservices, enabling partial saves and reducing customer drop-off. Has hands-on experience scaling and securing Python/FastAPI APIs (OAuth2/JWT, CORS), migrating cold data from MySQL to MongoDB via Kubernetes CronJobs, and implementing RBAC/RLS with Supabase + Postgres.”

“Backend/data engineer from Oscar Health specializing in healthcare claims systems on AWS. Built HIPAA-compliant real-time services (FastAPI/Postgres/Kafka on EKS) and serverless ingestion pipelines, and led modernization of a legacy SAS claims pricing system to Python/Spark with rigorous parity validation. Demonstrated measurable impact with high uptime/low latency services and major Snowflake performance and cost reductions.”

Pratham Thukral

Screened

Mid-level Software Engineer specializing in distributed systems on AWS

Seattle, WA3y exp

“Data/infra engineer with AWS DynamoDB experience who has shipped reliability-critical systems (Global Tables replica repair protocol) and customer-facing service rollouts using canary/percentage-based deployments, strong observability, and rollback strategies. Also built end-to-end Airflow pipelines producing weekly automated reports over ~10TB of advertising segment data, with rigorous week-over-week data quality validation.”

“Engineer with deep hands-on experience building Square's billing and payments platform in a startup-like environment inside a larger company. They drove a high-stakes PostgreSQL migration, built merchant-facing full-stack features across React/TypeScript, Go, and Python, and designed for PCI-compliant, high-throughput financial workflows with strong observability and production rigor.”

“Senior full-stack engineer with 5 years of experience across Bank of America, AT&T, and NextAI/XAI, building cloud-native, high-availability products spanning React, Node, Java, Kotlin, Python, and AWS. Particularly compelling for teams needing someone who can own architecture, implementation, DevOps, and UX polish end-to-end—from a real-time loan eligibility platform handling 50,000+ daily requests to live event dashboards that improved operations and helped drive $250K in ARR.”

Brian Sanders

Screened

Senior Backend Engineer specializing in GenAI, LLMs, and scalable data pipelines

Chicago, IL12y exp

“Backend/ML platform engineer from Snapsheet who owned production Python services and data pipelines for insurance claims, including an AI document classification/summarization FastAPI service on ECS/Fargate processing 1M+ documents/year. Strong in AWS infrastructure (Terraform, CI/CD, secrets/IAM, autoscaling), Glue/PySpark ETL with schema evolution controls, and legacy SAS-to-microservices modernization with safe, feature-flagged rollouts and measurable performance wins.”