Vetted Distributed Systems Professionals

Yash Prakashbhai Shah

Screened

Senior Backend Software Engineer specializing in Java, microservices, and cloud infrastructure

Santa Clara, CA6y exp

“Backend/platform engineer at Aryaka Networks who built a centralized resiliency and security Spring Boot library to standardize Keycloak RBAC and fault-tolerance across 25+ Kubernetes-migrated microservices. Uses profiling and observability (Prometheus/Grafana) to drive measurable performance and reliability gains (25% faster APIs, 70% faster environment setup) and accelerates adoption via golden-path starter repos and Swagger/OpenAPI live docs.”

Purva Chakravarti

Screened

Senior Full-Stack Software Engineer specializing in scalable web apps, cloud, and blockchain/AI

Chino, California11y exp

“Full-stack engineer with strong production ownership across React/TypeScript, Node.js, and AWS (EC2/ECS/RDS/CloudWatch), including CI/CD, observability, and incident response. Delivered a secure RBAC workflow module end-to-end and achieved measurable gains (~30–40% latency reduction, ~50% error reduction) that lowered infra/ops costs. Comfortable in high-ambiguity startup environments—shipped a payment module within 2 days of joining with no documentation.”

Michelle Gurovith

Screened

Intern Software Engineer specializing in iOS (Swift/SwiftUI) and distributed systems

Danville, CA1y exp

“Built a fault-tolerant distributed IoT sensor network on Raspberry Pi using a token-ring protocol, implementing leader election, timeout-based failure detection, and dynamic reconfiguration when nodes drop mid-round. Focused on reliability and data integrity, including exactly-once processing semantics backed by a MySQL backend and socket-level instrumentation to debug real-time coordination issues.”

Srinivasan Gomadam Ramesh

Screened

Mid-level AI/Data Engineer specializing in agentic AI and data platforms

Redmond, WA7y exp

“AI/LLM engineer who built a production resume-parsing and candidate-matching platform at Quadrant Technologies, combining agentic LangChain workflows, VLM-based document template extraction (~85% accuracy), and a hybrid RAG backend for resume-to-JD search. Notably integrated automated LLM evals and metric-based CI/CD quality gates to catch silent prompt/model regressions, and led a 3-person team across frontend/backend/testing.”

“Built and shipped AI products at Humanitarians AI, including a full-stack multi-agent platform that consolidated six faculty AI tools into one interface and achieved 100+ user adoption, 70% less workflow switching, and a 6x latency improvement. Also designed a grounded document parser using FAISS and structured LLM outputs that reduced hallucinations by 60%, showing strong depth in both product-minded engineering and production AI systems.”

“Front-end/full-stack engineer with about two years of experience building high-stakes internal trading operations tools for traders and operations engineers. Stands out for combining deep browser performance work, strong TypeScript/React architecture, and direct user observation to improve incident response workflows in live production environments.”

“Full-stack engineer with hands-on ownership of a production AI knowledge assistant used by 10,000+ daily users. Combines React/Next.js frontend work with FastAPI, AWS serverless, and RAG architecture using GPT-4, LangChain, and Pinecone, with measurable impact on relevance, latency, uptime, and support deflection.”

“Full-stack/AI engineer with very recent startup experience building creator and CRM AI platforms. They combine React/TypeScript frontend work with Python-based LangChain/LangGraph AI workflows and Go microservices, and have practical experience hardening third-party integrations through abstraction layers, versioning, monitoring, and alerts.”

Alex Archer

Screened

Staff Full-Stack Engineer specializing in Python, AI systems, and cloud SaaS

Anna, TX8y exp

“Full-stack startup engineer from a 20-30 person company who led a legacy monolith breakup into microservices, improving response times by 30% and database performance by 20%. Has hands-on experience across React/Next.js, TypeScript, Go, Python, and AI/data pipeline work, including building AI-driven platforms for freight and publisher-focused B2B SaaS products.”

“Backend Python engineer who has built an LLM agentic tutoring/assignment helper with a custom pipeline for parsing visually complex textbooks (integrating AlibabaResearch VGT and implementing missing preprocessing from the paper), improving RAG grounding with ~90% cleaner extracted text. Also led major platform scaling work by refactoring monolithic image processing into Celery-based async microservices on AWS (GPU/CUDA + S3), and implemented Kafka streaming for payment webhooks with strict ordering, idempotency, and multi-zone fault tolerance.”

“Co-founder at Skoolive who built a multi-agent LLM application to help users understand complex research papers (including PDF interaction and flowchart-style representations), moving from prototype to production using Gemini SDK and deployment to Runway. Also developed and demoed a web-agent benchmarking framework, running hands-on sessions with customer-facing teams to improve agent reliability and drive adoption.”

“CloudData engineer who productionized an LLM assistant for a warehouse/logistics customer by wrapping it as a versioned, containerized API with guardrails, deterministic post-processing, and full observability. Experienced diagnosing real-time RAG/agentic incidents (latency spikes and confident-wrong answers) using trace-based isolation, replay in staging, retrieval tuning, and canary releases. Regularly runs technical demos/workshops and partners with sales on security/IAM, SLAs, and pilot rollouts to drive adoption.”

“Engineering leader who modernized infrastructure by migrating a ~100-server co-location setup to AWS/GCP with IaC, auto-scaling, and fault-tolerant design, reducing hardware upgrade burden. Also led a key analytics architecture shift from MySQL to ClickHouse to enable highly granular ad revenue attribution and profitability insights, while scaling the dev org from 2–3 to ~12 with stronger CI/testing and review processes.”

Sharanya Rao

Screened

Mid-level Backend & Blockchain Engineer specializing in Cosmos SDK and EVM

Remote, USA4y exp

“Built and productionized an LLM+RAG lending assistant on AWS to help loan officers quickly answer questions from credit policies and prior decisions, tackling hallucinations with retrieval-only responses and a no-context fallback. Also automated end-to-end ETL and model retraining/deployment using Apache Airflow, and has experience translating clinical stakeholder needs (doctors/care managers) into ML features, metrics, and dashboards.”

Berkan Özgür

Screened

Senior XR Engineer specializing in spatial computing and cross-platform Unity systems

San Jose, CA9y exp

“XR/Unity developer who built an underwater experience (Visutate) featuring reactive flocking fish that respond to user presence and hand-feeding interactions. Also implemented multiplayer using Unity Netcode, addressing sync challenges via reduced streamed data and client-side prediction; prefers impactful work in startup-style environments.”

Jyothsna V

Screened

Mid-level Backend Software Engineer specializing in Python/FastAPI and cloud-native microservices

USA4y exp

“Backend engineer who evolved Coca-Cola bottlers' Trade Promotion Optimization platform at Coke One North America, building domain-focused microservices in Node.js and Python (Flask/FastAPI) with PostgreSQL. Experienced in multi-tenant security (OAuth2/JWT, RBAC, row-level scoping by bottler/region), API contract/versioning discipline, and Azure DevOps-driven incremental rollouts with strong observability.”

chandankumar ramamurthy

Screened

Junior Full-Stack Engineer specializing in LLM-powered products

Washington, D.C.3y exp

“Built multiple systems from scratch at DSSD and Aglint, including an NGO sustainability reporting dashboard and a production LLM-powered phone screening agent using Twilio/Retell AI with RAG grounded in PostgreSQL candidate/job data. Strong focus on real-world reliability: guardrails, monitoring, and lightweight eval/regression loops that reduced recruiter score overrides by ~30%. Currently on OPT through May 2026 (plans STEM OPT extension) and committed to relocating to NYC for in-person work; seeking $90k–$120k base with meaningful equity for founding engineer roles.”

“Full-stack product engineer focused on data-heavy dashboard applications, with hands-on ownership from React/TypeScript UI through Node/Express APIs to Postgres schema design and optimization. Stands out for combining product sense with engineering rigor: improving onboarding and reporting flows using analytics and user feedback, while also building reusable upload infrastructure and safe multi-tenant configurable experiences.”

“Senior engineer with experience at Micro Focus/HPE (now OpenText) supporting enterprise customers on monitoring platform deployments, upgrades, and ongoing product use. Brings hands-on expertise in operations agents, agentless integrations, security-related upgrade troubleshooting, and cross-functional escalation with engineering to keep customer environments stable and successful.”

“Full-stack product engineer with strong web3/blockchain experience, having built invoicing/tokenization, transaction explorer, and no-code workflow products across React, Node.js/serverless, and SQL. Stands out for combining deep technical execution with product thinking—improving onboarding completion by ~40%, shipping quickly under ambiguity, and creating reusable platform primitives for auditability and multi-tenant customization.”

Keeravani Chekuri

Screened

Mid-level AI/ML Engineer specializing in LLM systems and MLOps

Boston, MA3y exp

“Built and deployed an AI tutoring assistant end-to-end at Nexora School, spanning discovery with school districts, multi-agent LangGraph/RAG architecture, AWS Bedrock migration, and post-launch stabilization. Stands out for combining hands-on LLM systems engineering with strong educator-facing trust building, FERPA-driven architecture decisions, and disciplined production practices around evals, logging, and messy document ingestion.”

“At ReferU.AI, designed and deployed an agentic RAG pipeline that automates multi-jurisdiction legal document drafting, emphasizing hallucination reduction through hybrid retrieval, validation agents, guardrails, and iterative regeneration. Experienced with orchestration frameworks (especially CrewAI) and rigorous testing/evaluation practices including human-in-the-loop review, adversarial testing, and production metrics/logging.”

“Full-stack software engineer with hands-on experience shipping AI-driven product experiences, including a conversational travel planner and a RAG-based PDF question-answering system. Has also built enterprise automation APIs at Accenture for network diagnostics, combining backend engineering, testing automation, and user-focused product simplification for non-technical operations teams.”