Vetted Unit Testing Professionals

Sri Chandana Topuri

Screened

Mid-level Java Full-Stack Developer specializing in Spring microservices and Angular

5y exp

“Backend-focused engineer working primarily with Python/Django who also handles full-stack responsibilities. Has hands-on experience deploying containerized Python/Java microservices to Kubernetes using Helm and GitOps (ArgoCD), plus building Kafka-based event streaming with reliability controls (acks, consumer groups, DLQ). Also supported major on-prem to cloud/hybrid migrations using Terraform/Ansible with blue-green cutovers and data replication to minimize downtime.”

Weston Carpenter

Screened

Mid-level Backend Software Engineer specializing in distributed systems

San Francisco, CA6y exp

“Technical/presales engineer with experience at Grubhub and Appen, spanning LLM-adjacent data labeling workflows and production AI troubleshooting. Built an integrations platform at Grubhub and has hands-on experience diagnosing prompt-related AI failures via Splunk, adding JUnit tests and logging to prevent recurrence. Known for shipping customer-specific workflow adaptations (e.g., OCR annotation coordinate transformations for crop/rotation) while keeping timelines intact through iterative delivery and parallelization.”

Ashwini Ramesh Kumar

Screened

Junior AI Software Engineer specializing in LLMs, RAG, and agent workflows

Remote1y exp

“Backend/ML-leaning engineer who built a content-based event recommender for FlowMingle using embeddings + HNSW vector search on Google Cloud, with Firebase as the backend and a managed recommendation lifecycle (15 recs/user, daily async generation, weekly deletion) now serving 1500+ users. Also led a cost-driven migration of ConvAI services to Azure AI using parallel request testing from a Unity client, with post-migration monitoring via logs and model evals; contributed to a Massachusetts law-enforcement conversation analysis system by expanding ingestion to PDF/TXT/Excel and multi-file inputs.”

Luis Aragon

Screened

Senior Software Engineer specializing in data infrastructure and distributed systems

San Francisco, CA6y exp

“Software engineer working on agentic AI SMS customer engagement flows and a Customer Data Profile service that unifies journey data across SMS/web/calls while enforcing precise consent management. Has hands-on production operations experience, including recovering a reporting-critical Elasticsearch outage by standing up a new cluster in Kubernetes, restoring from snapshots, and rewinding Kafka consumers to reprocess missed data.”

Shweta Gupta

Screened

Senior Backend Software Engineer specializing in Java microservices, Kafka, and AWS

Seattle, WA6y exp

“AI engineer who shipped a production chat assistant for a storage company by building the underlying RAG-style knowledge base (document ingestion, chunking/embeddings, FAISS vector store) and an admin update interface to keep content current. Also has full-stack delivery experience (Python REST APIs + React/TypeScript UI) and AWS operations using Terraform/Jenkins, including handling a real production performance incident by optimizing DB queries and adding auto-scaling.”

Shashank Nawathe

Screened

Senior Front-End Engineer specializing in React, micro frontends, and GraphQL

Sunnyvale, CA8y exp

“Frontend engineer with Walmart Labs experience who contributed to the React Query (TanStack) open-source ecosystem by reproducing and helping fix a tricky cache invalidation edge case via a detailed GitHub issue and merged PR. Led measurable runtime performance improvements on a large B2B dashboard (D3.js), using memoization, component refactors, web workers, and virtualization to cut render time ~60% and eliminate UI freezes, and standardized data-fetching patterns to reduce data-related bugs ~30%.”

Sanjay Mandru

Screened

Mid-Level Full-Stack Software Engineer specializing in cloud microservices and real-time analytics

Buffalo, NY3y exp

“Software engineer who built a reusable React component package (UI modules, auth helpers, API client wrappers) for an AI SaaS background-removal project, emphasizing performance (tree shaking/dynamic imports) and reliability (Jest + Storybook). Also delivered a unified REST API for Samsung Big Data Portal, resolving cross-team issues by standardizing schemas, improving validation/logging, and operating effectively amid shifting requirements.”

Keerthi Kalluri

Screened

Senior Full-Stack & GenAI Engineer specializing in healthcare and financial services

6y exp

“Built and deployed a production LLM-powered customer support assistant using a RAG backend in Python, focused on deflecting repetitive Tier-1 tickets and reducing resolution time. Demonstrates strong production engineering instincts around reliability (confidence scoring + human fallback), scalability/cost optimization (multi-stage pipelines), and workflow orchestration/observability (LangChain, custom DAGs, structured logging, step metrics).”

Karan Javali

Screened

Mid-Level Full-Stack Software Engineer specializing in FinTech and cloud-native web platforms

Salt Lake City, Utah5y exp

“Software engineer with experience at Goldman Sachs and Arizona State University’s Learning Engineering Institute, shipping production backend systems including a vendor equities invoice-generation service designed for extensibility across multiple vendors. Built Django REST + PostgreSQL backends with JWT auth and Pytest coverage, and delivered data-heavy, responsive Angular dashboards; also has exposure to AWS EC2 deployments and GitLab CI/CD automation.”

Nikhitha santhoshi Maroju

Screened

Mid-level Full-Stack Software Engineer specializing in Java/Spring microservices on AWS

Redwood, CA4y exp

“Built and shipped a production LLM-powered fraud investigation agent using RAG to generate transaction explanations and draft analyst reports. Emphasizes production robustness (fallbacks, strict structured outputs, async orchestration, monitoring/evals) and reports measurable impact: ~12% precision lift and ~80 high-priority alerts per week with reduced manual effort.”

Anthony Thanpoovong

Screened

Entry-level Software Engineer specializing in cloud, AI, and full-stack development

Toronto, Canada1y exp

“Backend/AI engineer with hands-on experience building LLM-powered data products and AI platform workflows, including a project that turns tabular datasets into graphs, summaries, and chat-based insights with 1-2 second latency. Also contributed at TELUS to a Sovereign AI Factory self-serve onboarding platform tied to 100+ NVIDIA H200 GPUs, giving them an interesting mix of applied LLM, platform, and infrastructure exposure.”

Yuchen Wang

Screened

Intern Software Engineer specializing in full-stack development and AI/ML

New York, NY1y exp

“Built and maintains an AI Finance Tracker end-to-end as a solo full-stack product owner, from Figma designs and React frontend to Flask APIs, Firestore, auth, deployment, and AI insights. Stands out for combining product instinct with pragmatic engineering decisions like pre-aggregating financial data to control LLM costs and adding OCR receipt scanning based on real user feedback.”

“ML/AI engineer focused on taking LLM products from experiment to production, with hands-on ownership of a RAG-based customer support system that improved response quality by 35% and cut latency by 30%. Stands out for combining product impact with production rigor across retrieval tuning, safety guardrails, monitoring, and reusable Python/FastAPI services that accelerated adoption across teams.”

Brendan Dwyer

Screened

Senior AI/ML Engineer specializing in GenAI and cloud platforms

Colorado Springs, CO10y exp

“ML/AI engineer with hands-on experience turning research-style RAG concepts into production underwriting systems at Prudential Financial. Built an internal document intelligence assistant end-to-end with strong monitoring, safety, and evaluation practices, driving a 38% faster review process and 31% better retrieval accuracy. Also improved platform engineering at VivSoft by standardizing Python-based ML deployment across 60+ models.”

Sai Sreenath Kalva

Screened

Mid-level Full-Stack Software Engineer specializing in AI and Healthcare IT

Rosemead, CA5y exp

“Full-stack engineer with strong AI architecture experience in regulated healthcare environments, including a HIPAA-compliant conversational reporting assistant for LA County Department of Public Health and clinical workflow features for Oracle Health/Cerner PowerChart. Stands out for combining LLM/RAG system design, healthcare compliance, and production-grade reliability practices across Azure, AWS, and Kubernetes.”

“Software engineer with 4 years of experience spanning scalable backend systems, full-stack product development, and production LLM integrations in finance, insurance, and e-commerce contexts. They describe shipping an AI-powered internal financial analysis tool, improving document-review workflows by 40%, and driving a zero-to-one B2B SaaS subscription launch with cross-functional GTM alignment.”

“Full-stack engineer at an early-stage startup with hands-on production experience spanning Angular frontend features, backend safety checks for an image-generation workflow (OpenAI Safety), and AWS operations. Built CI/CD to ECS with GitHub Actions, implemented CloudWatch observability, and improved release reliability via Blue/Green deployments with automatic rollback.”

“Backend engineer in healthcare data systems who has owned production pipelines end-to-end, from ingesting patient and claims data to serving it through secure APIs. Brings a strong mix of Python, SQL, microservices, cloud deployment, and data reliability practices, with measurable performance gains and experience building resilient integrations with external data sources.”

Apoorva Swaminathan Iyer

Screened

Mid-level Software Developer specializing in full-stack engineering and application security

Raleigh, NC3y exp

“Developer who has evolved into an AI-native builder, using Claude, Copilot, Cursor, and multi-agent workflows as collaborators while retaining ownership of architecture and code quality. At OpenPRA, they ramped quickly into NestJS from a Spring Boot background and implemented OAuth/JWT security; on the Aha quiz app, they effectively acted as a tech lead for AI agents across feature delivery, debugging, CI/CD, and Dockerization.”

“Full-stack software engineer who has owned production workflows spanning React/Next.js, FastAPI, Redis-backed async processing, and PostgreSQL in a multi-tenant invoice-processing product. Shows strong product instincts as well—improving UX for long-running operations, iterating MVPs based on real user behavior, and balancing reusable abstractions with practical implementation constraints.”

“Founding engineer at an edtech startup who combines hands-on engineering leadership with advanced AI-native development workflows. They’ve built an AI grading pipeline and a multi-agent SDLC tool, and stand out for treating AI agents like an engineering team with planning, parallel execution, QA, and rigorous validation.”

Michael Boaz

Screened

Senior Software Developer specializing in cloud-native and event-driven architecture

Atlanta, GA24y exp

“Built and shipped production LLM/agent systems on AWS for internal developer support and IT observability use cases, including a Claude-based support tool grounded in internal documentation and a cost-optimized ServiceNow integration. Stands out for combining agent design, cloud architecture, CI/CD, chaos testing, and observability to make non-deterministic systems reliable and maintainable in production.”

“Backend engineer with hands-on ownership of Spring Boot microservice deployments in Freddie Mac's mortgage workflow domain, including measurable gains in reliability and MTTR. Brings strong production debugging skills around distributed transaction pipelines and has also built a full-stack AI chatbot project using React, Express, and Google Gemini API.”

“Backend engineer with experience at HSBC and Machinations who has delivered major production performance wins (cutting large trade-file upload times from ~13–15s to ~2s) using chunked parallel processing with strong reliability controls. Also built and shipped an applied AI RAG workflow using Langflow + Cohere embeddings + FAISS with hosted/local LLM fallbacks (Hugging Face, Ollama) and production-grade guardrails, observability, and evaluation.”