Vetted Distributed Systems Professionals

“Software developer who actively integrates AI coding tools like ClaudeCode, Codex, and ChatGPT into day-to-day development for brainstorming, planning, and reducing boilerplate work. They show thoughtful awareness of agent limitations such as hallucinations and use markdown-based project context files to improve output quality.”

“Built and shipped an end-to-end AI-powered portfolio chatbot, owning the React frontend, FastAPI backend, and FAISS-based retrieval layer. Demonstrates hands-on full-stack product thinking with attention to UI performance, TypeScript maintainability, and post-launch iteration on response relevance and speed.”

Meghkumar Patel

Screened

Intern-level Software Engineer specializing in backend, cloud, and AI systems

Vadodara, India1y exp

“MS Software Engineering candidate at SJSU with hands-on full-stack and applied AI experience, including building DataTrust, a secure enterprise RAG assistant with ABAC-style access control, audit logging, and grounded-answer evaluation. Also built CareerPilot, an AI interview-prep product that turns LLM and speech-to-text outputs into structured, user-friendly feedback for students and job seekers.”

“Software engineer with a strong builder mindset who has worked across ML, backend, and frontend systems. Notably built an AI-driven predictive autoscaler for Kubernetes from scratch using Prometheus, TensorFlow, Flask, and Spring Boot, and also delivered customer-facing automation features in financial document processing by working directly with auditors to translate domain rules into product logic.”

Hashim Kalam

Screened

Junior Software Engineer specializing in backend systems and applied AI

Colombo, Sri Lanka3y exp

“Full-stack and backend-oriented engineer with experience spanning customer-facing web products, LLM-based multi-agent systems, and enterprise Go microservices. They’ve worked on a ticketing/payments platform with Stripe, an NLP-to-2D-CAD MVP, and AI orchestration using LangChain, OpenAI, and Gemini, showing a mix of product thinking, backend architecture, and applied AI experimentation.”

SAUD SALEEM

Screened

Senior Python Engineer specializing in scalable backend and distributed systems

Stockton, CA6y exp

“Startup-oriented full-stack engineer who has worked across distributed systems, data, and compliance-heavy B2B SaaS products. They led an incremental migration from a monolith to an event-driven microservices architecture and also built high-volume healthcare ETL pipelines, giving them a strong mix of product engineering, platform modernization, and data-intensive backend experience.”

“Full-stack engineer who has shipped and operated generative-AI chat/QA features end-to-end, including a RAG-based pipeline with guardrails and cost/latency monitoring in production. Experienced with React/TypeScript + Node/Postgres architectures, Dockerized deployments to AWS (EC2) via GitHub Actions CI/CD, and building reliable ingestion/ETL systems with idempotency, backfills, and reconciliation.”

“Built and deployed a production RAG-based multilingual analytics assistant for healthcare operations, enabling non-technical teams to query claims/EHR and risk metrics with grounded explanations. Demonstrates strong end-to-end LLM system engineering (retrieval tuning, re-ranking, hallucination controls, verification layers) plus workflow orchestration (Airflow/Composer/Step Functions) and stakeholder-driven iteration via prototypes and dashboards.”

“Software/product engineer who owns customer-facing internal platforms end-to-end, with deep experience building data pipeline health and data quality tooling (near-real-time alerting and ops dashboards). Strong in React/TypeScript + Python REST architectures and microservices with RabbitMQ, emphasizing reliability patterns (idempotency, DLQs, correlation IDs) and fast, safe iteration via feature flags, testing, and observability.”

“Backend engineer who owned the API layer for an AI trust/analytics dashboard (trust scores, stability checks, public verification endpoints) using Python/FastAPI and Postgres. Has hands-on DevOps experience deploying FastAPI and Node.js services to AWS Kubernetes with GitHub Actions + ArgoCD GitOps, plus Kafka-based real-time event streaming and careful staged migration practices (shadow traffic/dual writes, rollback planning).”

“Entrepreneur with 20+ years in the recruiting industry building a Salesforce-based CRM tailored to track candidate outreach from initial identification (positioned as a differentiated alternative to traditional ATS workflows). Previously launched a small consulting company after spotting unmet technical needs among small medical practitioners, emphasizing branding and relationship-driven business development.”

“Product-minded engineer who has owned features end-to-end, including a full onboarding redesign that lifted completion ~25% and a production LLM/RAG report-generation system with strong guardrails (schema-constrained JSON, confidence gating, logging) and an automated eval/regression loop built from real user queries. Also built a scalable research data pipeline ingesting messy PDFs/JSON/CSVs with normalization, idempotent reruns, observability, and cost/latency tradeoffs.”

“Full-stack engineer who shipped a production real-time code editor using Next.js App Router (server components for MongoDB fetch + client components over WebSockets) with optimistic updates and concurrency conflict handling. Also designed a multi-tenant Postgres subscription billing data model and validated analytics query performance with EXPLAIN ANALYZE; reports a ~25% improvement in supported concurrent sessions via MongoDB/schema optimization.”

“Software engineer who built an AI marketing/outreach agent end-to-end: Next.js (App Router + TypeScript) frontend integrated with a Python/Django REST backend using LLMs (Gemini, ChatGPT-4o) and SQL databases. Demonstrated measurable performance wins—improved a 100k-record UI by 15% (Lighthouse) and cut a Postgres-backed search API from ~3s to ~1ms via indexing—while also owning post-launch monitoring (webhooks/cron, New Relic/CloudWatch) and customer support.”

Yashwant Gandham

Screened

Junior Machine Learning & Backend Engineer specializing in LLM systems and ML infrastructure

Boulder, CO1y exp

“Built and deployed production RAG-based document search/Q&A systems (DocChat and an internship marketing RAG), using a React + FastAPI stack on GCP with docs stored in GCP buckets and retrieval via embeddings/vector DB. Emphasizes cost/performance tradeoffs (reported ~40% cost reduction) and ships via Docker (Railway), with load/API testing using JMeter and Swagger; regularly collaborates with a CEO stakeholder to iterate and push changes to production.”

Avanishika Revelli

Screened

Junior Software Engineer specializing in backend, cloud, and robotics automation

2y exp

“Graduate Research Assistant in Robotics at Arizona State University who built an end-to-end LLM-driven task execution framework enabling collaborative robots to convert high-level natural language instructions into safe, executable ROS actions. Implemented robust monitoring, failure detection, and automatic replanning, and addressed real-world issues like timestamp/frame-transform mismatches and heterogeneous robot interoperability using adapter nodes.”

Gomathy Selvamuthiah

Screened

Junior Data/AI Engineer specializing in MLOps, real-time pipelines, and LLM applications

Portland, US2y exp

“Built an LLM-driven MLOps agent at SBD Technologies that automated an EV-charging prediction workflow end-to-end, integrating with real-time Kafka/FastAPI systems supporting 120K+ chargers at 99.99% event delivery. Addressed frequent schema drift by implementing SQLAlchemy/Flyway validation (60% reduction in drift issues) and deployed as Kubernetes microservices with GitHub Actions CI/CD; also has Airflow-based ingestion/crawling experience into Snowflake and stakeholder-facing delivery via a Fleetcharge PWA.”

“Product-minded full-stack engineer with experience in fintech identity verification and industrial analytics, focused on turning repeated operational pain points into reusable platforms. Built real-time KYC/KYB dashboards, secure cross-platform web components, and a multi-tenant workflow engine that cut onboarding from 2 weeks to 1 day while materially improving conversion, reliability, and developer speed.”

I Anuj

Screened

Junior Backend/Infrastructure Engineer specializing in AWS distributed systems

Chennai, India2y exp

“Backend engineer with 1.7 years of experience plus prior founding experience who has already owned production systems end-to-end in an early-stage environment. Most notably, they rebuilt a failing ingestion pipeline into a stable SQS/Fargate architecture that improved success from 40% to 100%, boosted throughput 10x, and cut processing time by ~75%, while also shipping an LLM-powered fashion search workflow using Vertex AI and Elasticsearch.”

“Software/product engineer who has owned a consumer iOS dating app from customer discovery through roadmap execution, while also shipping an in-app LLM-powered support/feedback bot. Brings a mix of product sense and backend systems experience, including rebuilding a race-condition-prone event orchestration system and designing microservices to handle arbitrary black-box production data.”

“Software engineer with hands-on experience spanning backend APIs, streaming data systems, and cloud/infrastructure automation, who is already using agentic AI workflows in a disciplined way. Stands out for combining practical systems work in Spring Boot, Kafka/Spark/ClickHouse, and Terraform/Kubernetes with a thoughtful approach to AI oversight, architecture, and multi-agent orchestration.”

Sampath achalla

Screened

Mid-level Systems Software Engineer specializing in distributed cloud infrastructure

USA3y exp

“Backend-leaning full-stack engineer in fintech/payments who shipped an end-to-end Stripe payments + webhook system for a financial microservices platform, emphasizing ledger accuracy via idempotency, transactional writes, retries, and DLQs. Also delivered a real-time React/TypeScript payment status dashboard informed by user interviews, and improved production performance by 35% p95 latency through PostgreSQL tuning and Redis caching on AWS.”

Tejal Patel

Screened

Intern Software Engineer specializing in full-stack and backend systems

New York, USA5y exp

“Full-stack developer intern who significantly owned parts of a recruitment platform used by recruiters, job seekers, and company administrators. They stand out for building and optimizing complex React-based dashboards for large datasets, improving responsiveness through debouncing, memoization, reusable component architecture, and thoughtful UX simplification.”

“Backend-focused engineer with 7+ years of experience building cloud-native, distributed SaaS systems in startup-like environments, including healthcare and enterprise automation platforms. Strong in Go/Python microservices, event-driven architectures, and production AI/LLM integration, with hands-on experience scaling Kubernetes-based systems on AWS while balancing speed, reliability, and evolving product requirements.”