Vetted Batch Processing Professionals

“AI engineer who built an agentic, production-deployed LLM workflow for tobacco violation parsing and automated multi-case creation, using six specialized agents and a human-in-the-loop confidence-threshold routing design. Addressed data privacy constraints by generating synthetic datasets with LLM prompting, and orchestrated reproducible end-to-end pipelines in LangChain with robust testing and evaluation (precision/recall, micro-F1).”

Hamna Anwar

Screened

Senior Full-Stack Engineer specializing in Go backend systems

Hayward, CA8y exp

“Full-stack/backend engineer with startup-style experience spanning healthcare and B2B infrastructure SaaS. Has worked across Python, Go, and React/TypeScript, including migrating services from Node.js to Go, building microservices and dashboards, and delivering measurable API performance gains through database tuning and Redis caching.”

“Backend/AI engineer who built and refactored a production RAG system over IRS Form 990 filings for 60 nonprofits, using a dual-path architecture (deterministic financial ranking + TF-IDF semantic retrieval) to keep latency sub-2s and reduce hallucinations. Demonstrates strong API craftsmanship in FastAPI (contract-first, OpenAPI-driven) plus production-grade security for multi-tenant systems (JWT, RBAC, Supabase-style RLS) and careful migration practices (feature flags, traffic mirroring, incremental rollout).”

“Frontend-focused engineer who built the entire UI architecture for a GenAI product as the sole founding engineer, shipping a unified experience across iOS, Android, and web. Stands out for combining cross-platform Flutter expertise with browser-level performance tuning, accessibility, and design-system thinking, including measurable wins like 45% faster load times, 94% accessibility, and dramatically faster engineer onboarding.”

“Backend Python engineer who owned a real-time manufacturing insights streaming service, building FastAPI async microservices with Kafka-style queue buffering, batching/backpressure, and a low-latency snapshot store. Led a serverless-to-Kubernetes (EKS) migration at UGenomeAi using GitOps-style GitHub Actions pipelines, standardized config/secrets, and improved deployment consistency with pinned dependencies and multi-stage Docker builds.”

“Built and shipped production AI features in the automotive dealership domain, including an end-to-end computer-vision damage detection system for trade-ins and a tool-calling, RAG-enabled LotSync AI Agent that answers inventory/VIN questions using strict schemas and internal APIs to avoid hallucinations. Also developed a Dagster + Oracle automated reporting pipeline as a Graduate Research Assistant, supporting 15+ university departments with normalized, reliable ETL workflows.”

Dhairya Gajjar

Screened

Mid-Level Software Engineer specializing in Healthcare Data Platforms

Remote2y exp

“Backend/ML engineer with healthcare domain experience building secure Medicare/Medicaid data APIs and real-time patient risk scoring. Shipped an end-to-end ML pipeline (scikit-learn/XGBoost) served via SageMaker and integrated into Flask APIs, with strong production reliability practices (Kafka schema validation, regression replay, observability, drift monitoring, and human-in-the-loop guardrails).”

Vinith Nagelly

Screened

Mid-level Full-Stack Developer specializing in Python/Django and React

Little Rock, AR4y exp

“Backend engineer at Hexanika who owned a real-time fraud-detection platform: built Django microservices, integrated a GenAI anomaly-scoring model, and optimized data/infra for low-latency production (including ~40% query-latency reduction). Experienced running containerized services on AWS/GCP with Kubernetes/GKE, GitHub Actions-based CI/CD + GitOps, and building Pub/Sub streaming pipelines and on-prem-to-cloud migrations.”

“Engineer with growth-stage startup experience on a 6-7 person cross-functional team, working across backend, data, and frontend systems. They’ve driven concrete improvements to high-volume data ingestion pipelines through batch processing and database optimization, and have built B2B SaaS data platforms for enterprise customers with multi-tenant support, integrations, and scalable backend services in Python and Go.”

Divya Patel

Screened

Mid-Level Software Engineer specializing in .NET and CMS platforms

Fremont, CA6y exp

“Built and owned end-to-end systems for the Department of Water Resources and NAHC, including a debt infrastructure management system and a TypeScript/React + .NET 6 CMS. Strong in shipping quickly with quality (CI/CD, automated testing), optimizing SQL Server performance for large datasets, and implementing microservices-style async processing with reliability patterns (retries/idempotency/monitoring). Also delivered widely adopted internal workflow automation and reporting using Power Automate and Power BI.”

“Built and shipped a production LLM-powered document processing agent (ingestion→OCR→LLM extraction/classification→validation→DB/workflow triggers) using Kafka and PostgreSQL. Emphasizes production reliability with strict JSON schemas, idempotent services, retries/backoff, fallback models, and human-in-the-loop review—driving ~90% automation, minutes-to-seconds processing, and ~10x throughput.”