Vetted Amazon S3 Professionals

JUNG NO

Screened

Senior Solutions Engineer & Applied AI Builder specializing in agentic workflows

Remote, US9y exp

“Built and shipped a production AI booking/quoting system for a Spanish-speaking cleaning business serving English-speaking customers, covering the full booking and payment flow and generating bilingual SEO/AEO content. Uses Gemini/Genkit with multi-agent orchestration (ADK/MCP, LangChain) and a production stack on Vertex AI + Cloud Run + Terraform, with analytics wired from Google Analytics to BigQuery for measurable agent performance.”

Anil Babu Bollina

Screened

Senior Computer Vision Engineer specializing in industrial automation and 2D/3D perception

Nashville, TN8y exp

“Machine-vision engineer who designed an end-to-end inline inspection station for white wood pallets, combining laser line profilers with 2D color line-scan imaging to detect protruding nails (~2mm threshold) at conveyor speeds. Solved real production constraints (lighting reflections, per-trigger depth/color alignment, barcode tracking) and improved system accuracy from ~80% to 99.5% using barcode symbology changes and Keyence reader AI features.”

Shiva Dasi

Screened

Mid-level Software Engineer specializing in LLM agents and cloud-native systems

Boston, MA4y exp

“Built and shipped production LLM agents in compliance-sensitive environments (FERPA), emphasizing reliability via structured outputs, state-graph orchestration (LangGraph), and CI-driven eval/regression testing. Also has experience hardening messy ERP ingestion pipelines at scale (50K monthly orders) with normalization, idempotency/deduplication, and robust failure handling using AWS (SQS/CloudWatch) and PostgreSQL.”

Mrudula Devaguptapu

Screened

Mid-Level Software/AI Engineer specializing in backend systems, data pipelines, and RAG automation

United States3y exp

“Backend engineer with experience modernizing high-traffic subscription and payment systems (TCS) by moving to event-driven Spring Boot microservices with Kafka, adding idempotency/state management to eliminate duplicate processing. Built and scaled FastAPI services for AI automation workflows (360DMMC) with versioned contracts, JWT security, and strong observability, and has led live refactors using feature flags, parallel runs, and data reconciliation.”

Nidhi Sura

Screened

Junior Software Engineer specializing in AI platforms, distributed systems, and cloud infrastructure

Dublin, CA1y exp

“Software engineer with limited robotics background but deep experience building end-to-end document ingestion and image understanding systems, including a CAD-specific pipeline using a custom model to extract components and bounding boxes for user-facing visualization and Q&A. Also brings strong infrastructure/DevOps skills (Docker, Kubernetes, GitHub Actions, Terraform) with emphasis on reliability, cost optimization, and uptime.”

Ashay Panchal

Screened

Mid-level Software Engineer specializing in AI-driven distributed systems

San Jose, CA4y exp

“Backend engineer who built a high-stakes, privacy-first platform at be Still Analytics for survivors of domestic violence, emphasizing anonymity, security, and reliability. Experienced with GenAI backends (LangChain + AWS Bedrock) including RAG to prevent hallucinations, plus cloud-native scaling (Docker/Kubernetes) and cost-saving migrations from legacy VMs to serverless (30% reduction).”

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.”

Kundhana Paruchuru

Screened

Mid-level Data Scientist specializing in ML, LLM pipelines, and MLOps

Remote, USA3y exp

“Built and deployed a production LLM-driven document understanding pipeline using LangChain/LangGraph, focusing on reliability via step-by-step prompting, validation checks, and monitoring. Also partnered with non-technical marketing stakeholders at Heartland Community Network to deliver an XGBoost targeting model surfaced in Power BI, improving campaign conversion by 12%.”

Nagendra Reddy Palugulla

Screened

Mid-level Machine Learning Engineer specializing in LLMs, RAG, and MLOps

Florida, United States4y exp

“Built and shipped a production real-time content moderation platform for Zoom/WebEx-style meetings, combining Whisper speech-to-text with fast NLP classifiers and REST APIs to flag hate speech, bias, and HIPAA-related content under strict latency constraints. Demonstrates strong MLOps/infra depth (Airflow, Kubernetes, Terraform/Helm, observability) and a pragmatic approach to reducing false positives via threshold tuning, context validation, and hard-negative data—while partnering closely with compliance and product stakeholders.”

Yash Amre

Screened

Intern Data Scientist specializing in machine learning and NLP

California, USA1y exp

“Analytics-focused early-career candidate with internship experience owning reporting and system performance analysis projects end to end. They combine SQL data preparation, Python automation, and dashboard delivery with measurable impact, including roughly 50% less manual reporting and about 20% better forecast accuracy.”

“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.”

“Backend-focused engineer with experience at Ramp, Easebuzz, and George Mason University, spanning data pipelines, workflow automation, and production reliability. Stands out for quantifiable performance gains, strong debugging instincts in distributed job systems, and translating ambiguous finance operations processes into measurable automation outcomes.”

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.”

“Built and deployed a full-stack web product for international football fans visiting the U.S. for FIFA, owning everything from crawling and aggregating event data to frontend, backend, deployment, and maintenance. Particularly strong in data-heavy product work, using LLMs, Google Maps API, and SQL/RPC patterns to improve data quality, speed implementation, and support a polished user experience.”

Abhishek Ghaisas

Screened

Intern-level Data Scientist specializing in AI and full-stack applications

Pune, India1y exp

“Engineer with hands-on experience building production ML and Python backend systems, including a real-time social media monitoring pipeline handling 1000+ events per second and a prototype AI operations assistant for Seattle-Tacoma Airport. Stands out for combining reliability engineering, automation, and LLM/NLP-to-SQL work, with measurable impact such as improving uptime from 92% to 99.4%.”

“AI-focused software engineer who has built production CRM intelligence features including audio transcription, summarization, and action-item extraction, plus a multi-agent LLM/NLU pipeline using Supabase, Node.js, RabbitMQ, and CloudWatch. Stands out for a disciplined approach to AI-assisted coding: treating AI like a junior developer, rigorously testing outputs, and refining prompts to prevent hallucinations in real business workflows like resume screening.”

“Engineer with hands-on experience modernizing healthcare platform authorization and EVV compliance workflows, including replacing hardcoded permissions with a Cerbos-based RBAC/ABAC system. Stands out for pragmatic AI-assisted development in regulated environments, with a strong emphasis on testing, auditability, and catching subtle business-rule failures before production.”

“Builder of practical AI-backed products across developer tooling, travel search, defense, and healthcare-style workflows. They shipped an MCP/FastAPI/Gemma context-compaction system that cut token usage by about 80%, built a flight-price AI layer that validates LLM output against live search data, and helped shape a visionOS command center for a military air wing.”

“Built GRETA, a full-stack multi-agent AI platform for SEO content analysis and blog-writing support, combining React/TypeScript, serverless GCP Cloud Run workflows, and LLM/tool orchestration at scale. The system reportedly reduced manual analysis by 60%, and the candidate shows strong hands-on experience shipping AI products in ambiguous environments and refining them through internal user feedback.”

“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.”

Atharva Jagtap

Screened

Junior Full-Stack Software Engineer specializing in cloud and AI/ML applications

United States, Remote2y exp

“Full-stack engineer with hands-on experience across e-commerce personalization, enterprise RAG assistants, and cloud infrastructure automation. They’ve shipped AI features using Azure LLM APIs and vector search, improved recommendation engagement, and worked across frontend, backend, ML-informed analytics, and AWS infrastructure in early-stage environments.”

“Full-stack engineer with startup SaaS experience building workflow automation and case management platforms for business operations teams. Strongest in Python, TypeScript/React, and PostgreSQL, with hands-on ownership from backend architecture and APIs to production deployment on AWS; notably helped reduce manual processing and improve customer turnaround times in a high-ambiguity scaling environment.”