Vetted Unit Testing Professionals

Dhyey Desai

Screened

Intern AI/ML Engineer specializing in RAG, multimodal AI, and LLM systems

Los Angeles, California0y exp

“Built and shipped 'PetPulse,' a production AI pet-health note system that records voice notes, transcribes them, converts transcripts into structured symptom/event data, and supports grounded Q&A over a user’s notes and vet PDFs. Demonstrates full-stack LLM product execution (FastAPI + GPT-4 + Firebase), with concrete reliability/performance work (async endpoints, caching, RAG/embeddings, function calling) and user-centered iteration with a non-technical product stakeholder.”

SaiTeasmitha Kaja

Screened

Mid-level Full-Stack Software Engineer specializing in Java/Spring Boot and cloud microservices

Houston, TX4y exp

“Backend-focused Python/Flask engineer who has built authentication/profile services with clean modular architecture (blueprints + service layer) and tuned SQLAlchemy/Postgres for scale using indexing, query rewrites, and pagination. Has production-style integration experience for AI/ML via TensorFlow Serving and OpenAI APIs (batching, rate limiting, caching), plus multi-tenant data isolation and high-throughput background processing with Celery/Redis and idempotent jobs.”

Ganesh Bandi

Screened

Mid-level AI Engineer specializing in LLMs, RAG, and MLOps

USA6y exp

“LLM engineer who has deployed production RAG systems for regulated document QA (PDFs/knowledge bases), emphasizing grounded answers with citations, RBAC, monitoring, and continuous feedback. Demonstrates deep practical expertise in retrieval quality (semantic chunking, hybrid BM25+embeddings, re-ranking), reliability (guardrails, deterministic workflows), and measurable evaluation (golden sets, log replay, A/B tests) while partnering closely with compliance/operations stakeholders.”

Satwik Alla

Screened

Mid-level Full-Stack Software Engineer specializing in scalable APIs and real-time AI apps

United States of America3y exp

“Lead software engineer (3+ years) who built and scaled an AI product backend at Cosmo AGI from the ground up using FastAPI/Postgres/Redis/vector DB, targeting sub-200ms latency and supporting 1000+ active users. Strong in production-grade security and observability (OAuth/JWT, RBAC, Postgres RLS, Prometheus/Sentry), plus DevOps automation (Docker, GitHub Actions, blue-green deploys) with measurable impact on uptime, incidents, engagement, and deployment speed.”

Edgar GranadosOsegueda

Screened

Mid-level Robotics Researcher specializing in kinodynamic motion planning

Rutgers, USA7y exp

“Robotics software engineer focused on real-time estimation/control and motion replanning, currently integrating a factor-graph-based estimation/control stack with sampling-based replanning in a ROS environment validated on both MuSHR hardware and MuJoCo simulation. Strong in distributed-system debugging (rosbags/logging, controlled test scenarios) and ROS performance patterns (nodelets, TF/TF2), with prior multi-robot experience from SSL RoboCup using custom UDP protocols.”

Sragvi Vadali

Screened

Junior Software Engineer specializing in AI/ML and real-time systems

2y exp

“Backend/AI engineer who built a real-time vector database system for high-frequency financial data using Kafka/Flink on Kubernetes, achieving sub-100ms similarity search at 10k+ concurrent load and resolving tricky duplication issues with idempotency/versioning. Also shipped an end-to-end LLM-based travel itinerary feature (profiling + prompt workflows + APIs) with a focus on quality consistency and low latency.”

Utkarsh Srivastava

Screened

Junior Machine Learning Engineer specializing in LLMs, RAG, and medical imaging

New York City, USA3y exp

“At Fileread, the candidate built and deployed an LLM-powered legal document classification and retrieval layer for an agentic extraction system that turns unstructured legal PDFs into structured tables with line-level citations. They productionized a RAG-style pipeline (ingestion, embeddings, retrieval, reranking, generation) and report 95%+ F1 across 70+ legal categories, emphasizing rigorous evaluation and close collaboration with legal domain experts for high-stakes precision.”

Sai Charan Kolla

Screened

Mid-level AI/ML Engineer specializing in LLMs, RAG, and MLOps on AWS

TX, USA5y exp

“LLM engineer who built a production document intelligence/RAG pipeline to extract structured data from thousands of unstructured PDFs, cutting manual review time by 60%. Experienced with LangChain and Airflow orchestration plus rigorous evaluation (labeled datasets, prompt testing, HITL review, monitoring) to improve accuracy and reduce hallucinations while partnering closely with non-technical operations stakeholders.”

“Backend/data engineer with experience at Citi and Elevance Health, building end-to-end pipelines and data services in regulated, high-volume environments. They combine Python, SQL, .NET, Azure Functions, and strong observability/reliability patterns to improve processing speed, reduce manual effort, and maintain high uptime across financial and healthcare data platforms.”

“Backend/AI workflow engineer who built production-grade orchestration systems for hardware security verification at Silicon Assurance (Nextflow/Python/Postgres) and a multi-agent LLM-driven regulatory code checking system at the University of Florida. Emphasizes reliability: strict plan/execute/verify boundaries, queue-based isolation, and strong observability/auditability with Prometheus/Grafana and persisted prompts/tool calls.”

“Unity/C# game engineer with about 3 years of experience who owned a high-impact runtime content delivery platform at Zynga/Singa powering LiveOps releases for roughly two years. Their work cut app size by 35-40%, removed a 25K daily activator drop on release days, improved load times by 25%, and supported a feature that drove 10% quarterly revenue growth.”

Pahuldeep Singh

Screened

Senior Full-Stack Developer specializing in scalable web platforms and automation

Remote6y exp

“Backend/full-stack engineer focused on TypeScript/Node.js systems, with hands-on ownership of a real-time telemetry and dashboard platform built on Kafka, Debezium, PostgreSQL, and GraphQL. Stands out for combining event-driven architecture, correctness/idempotency patterns, strong observability, multi-tenant security, and developer-friendly API design in production environments.”

“Built a Flask-based web application for NCAA Men's gymnastics and also worked on a survey-question collection and normalization project for UC Berkeley's Cameron Institute. Shows a clear reliability mindset through validation, testing, logging, and error handling, and is comfortable turning ambiguous, messy data workflows into stable applications.”

Sergio Nunez

Screened

Senior Unity Engineer specializing in XR, mobile, and AI avatar experiences

Los Angeles, CA9y exp

“Unity/C# game engineer from Genies who built the avatar wearable customization system for Silver Studio and supported AI companion features through client-side LLM integrations. Stands out for combining clean architecture, analytics-driven product thinking, and practical optimization work across latency, AI cost controls, and mobile performance.”

Sachin Komati

Screened

Mid-level AI/ML Engineer specializing in GenAI, RAG, and healthcare ML

Florida, USA5y exp

“Built an end-to-end GenAI/RAG platform for financial compliance and research at BlackRock, focused on safe, auditable answers in a highly regulated environment. Combines strong LLM engineering depth with production platform skills and delivered clear business impact, including reducing research/compliance turnaround from hours to seconds, improving retrieval relevance by 22%, and cutting inference costs by 75%.”

“AI/ML-focused engineer with practical experience building RAG-based and multi-agent systems, including architectures for retrieval, reasoning, context processing, and response generation. Stands out for combining LLM productivity gains with disciplined software engineering practices like validation, monitoring, and reproducibility.”

“Frontend architecture leader with experience at Citi and Warner Bros. Discovery, building high-performance browser UIs for demanding enterprise and media workflows. Stands out for combining design-system standardization, deep browser performance optimization, and measurable impact: ~50% frontend improvement and 40% faster feature delivery across a 20+ engineer team.”

Deepthi Pamisetty

Screened

Mid-level Full-Stack Engineer specializing in FinTech and cloud-native systems

Dallas, TX6y exp

“Full-stack engineer with production experience building AI-powered search and automation systems at JPMorgan Chase and customer-facing product features at Wayfair. Stands out for combining React frontend work with backend microservices, RAG/LangChain AI integration, and cloud-scale performance tuning, including a support chatbot that reduced ticket resolution time by 35%.”

Pujan Parikh

Screened

Staff Front-End Engineer specializing in enterprise cloud and AI-driven applications

Redwood City, CA8y exp

“Frontend-leaning architect with deep React/TypeScript expertise who has repeatedly owned platform-level problems across Oracle Health, Oracle Cloud, and Veritas. Stands out for building cross-plugin routing standards for a next-gen EHR, high-scale real-time observability dashboards, and even stepping into backend/AI infrastructure design with Kafka- and RAG-based systems.”

“Full-stack engineer whose strongest hands-on work is a self-built real-time collaborative code editor spanning React, Node.js, Express, and WebSockets. They stand out for owning both product UX and backend synchronization challenges, with a clear bias toward simplicity, low-latency collaboration, and modular architecture in early-stage product building.”

“Backend/data engineer with strong AWS production experience across containers (ECS) and serverless (API Gateway/Lambda/SQS), plus Glue-based ETL to Parquet for Athena/Redshift. Demonstrates hands-on reliability and security depth (Cognito OAuth2/JWT with JWKS rotation, idempotency/DLQs, monitoring) and measurable performance wins (Redis caching + query tuning), along with legacy-to-services modernization using parallel-run parity and feature-flagged cutovers.”

“Backend engineer with hands-on experience scaling a Python/Flask incident-logging platform processing thousands of daily logs. Strong in performance tuning (PostgreSQL/SQLAlchemy query optimization, partitioning, summary tables) and reliability patterns (Redis caching, Celery background workers, Docker + Jenkins CI/CD), with some multi-tenant data isolation experience via separate DBs/schemas.”

“Backend engineer at Goldman Sachs who deployed internal LLM-powered utilities to summarize operational logs/tickets, with a strong emphasis on data sensitivity and reliability. Built deterministic workflows with template-based prompts, confidence checks, and rule-based fallbacks, and used monitoring plus failure-rate metrics to tune performance; also has hands-on Temporal orchestration experience for resilient async backend jobs.”

“Software engineer working on an e-commerce platform, currently building a RAG-based recommendation system with a team new to the technology. Has delivered an end-to-end React/TypeScript website for a local car dealer and built an internal "encryption as a service" tool to secure sensitive data across repositories and through release/UAT, with experience debugging microservices integration issues.”