Vetted Performance Optimization Professionals

“Full-stack engineer with production experience building and owning high-traffic e-commerce checkout flows in Next.js (App Router) + TypeScript across microservices (REST/GraphQL). Demonstrated measurable performance wins (30% checkout improvement; 85% initial load reduction at 20th Century FOX) and strong production rigor (APM/logs, CloudWatch, Postgres indexing + EXPLAIN ANALYZE), including offloading PDF generation to AWS Lambda.”

“Founding engineer at a civic-tech startup (Barrow) who built and operated a Next.js/TypeScript product with map-based public reporting, including clustering and dynamic geospatial loading to improve UX and performance. Also implemented a location-aware RAG chatbot using Pinecone, web scraping/transcription, caching, and fallback web search, and owned post-launch observability plus scaling decisions (load balancing/horizontal scaling) based on API usage patterns.”

Anvith Reddy Dodda

Screened

Mid-level AI Engineer specializing in GenAI, NLP, and MLOps

Remote, USA3y exp

“LLM/agentic-systems engineer with PayPal experience hardening an LLM-powered fraud support assistant from prototype to production, focusing on low-latency distributed architecture, rigorous evaluation/testing, and security/compliance. Comfortable in customer-facing and GTM contexts—runs technical demos/workshops, builds tailored pilots, and aligns sales/CS with engineering to close deals and drive adoption.”

Mithilesh Gaurihar

Screened

Mid-Level Software Engineer specializing in Java microservices and cloud-native systems

USA4y exp

“Full-stack engineer (SAP Labs experience) who built an end-to-end, real-time fraud detection system on Java 11/Spring Boot microservices with Kafka event streaming and a React/Redux analytics dashboard with WebSocket updates. Demonstrated strong production ownership by diagnosing a critical memory leak with Prometheus/CloudWatch + heap dumps and improving performance with Redis caching (40% faster queries), while also modernizing deployments via Kubernetes, Jenkins CI/CD, and Terraform.”

Prateeksha Ranjan

Screened

Mid-level Software Engineer specializing in embedded AI and full-stack systems

Irvine, California4y exp

“Robotics software engineer who built and owned core navigation components for a TurtleBot in ROS/ROS2 and Gazebo, including an RRT-based planner, waypoint-to-velocity motion planning, and PID trajectory tracking. Demonstrates strong real-time debugging skills (control-loop timing under CPU load), costmap/occupancy-grid tuning, and distributed ROS2 communication design using DDS/QoS, plus Docker and CI/CD automation experience from Keysight.”

Jahnavi Bellapukonda

Screened

Mid-Level Software Engineer specializing in full-stack web and cloud systems

Remote, USA3y exp

“Full-stack engineer with strong data engineering and privacy-domain experience, having owned an automated Data Subject Rights (DSR) processing pipeline end-to-end across Azure SQL and GCP (GCS/BigQuery). Emphasizes production reliability via idempotency, validation checkpoints, structured logging/monitoring, and safe CI/CD-driven deployments, and has also built React+TypeScript + Node/Postgres web apps with scalable, maintainable architecture.”

Sandeep Mekala

Screened

Director-level Mobile Engineering Manager specializing in Generative AI and agentic mobile experiences

Remote13y exp

“iOS player-coach who led end-to-end development of real-time customer support chat and unified notification systems for T-Mobile’s iOS app using SwiftUI, Firebase, WebSockets, and Core Data (including offline handling). Drove measurable reliability/latency gains (~30%) through a major notification refactor and owned a high-severity push-notification incident from rollback through RCA and backward-compatible hotfix, while also scaling team process and people management.”

Guojian Wang

Screened

Entry-Level Full-Stack Software Engineer specializing in React/Next.js and Node.js

United States0y exp

“Full-stack engineer with hands-on experience building and owning production e-commerce features in Next.js (App Router) + TypeScript, including SSR-driven category browsing with pagination and region-specific pricing. Strong focus on post-launch reliability and performance—optimizes React rendering (lazy loading/Suspense), tunes Postgres queries with indexes/explain plans, and supports durable order-processing workflows with idempotency, retries, and structured logging.”

“Founder/CTO-type startup leader who has built cloud-native data and AI platforms from scratch while owning both technical vision and product direction. Brings rare end-to-end startup experience spanning zero-to-one building, growth-stage execution, and fundraising from early stage through exit, with a strong ability to translate technical complexity into clear investor narratives.”

“Candidate is not currently pursuing a startup and has no familiarity with the VC/accelerator ecosystem, but shows a thoughtful founder mindset centered on building from scratch, evaluating user impact and implementation feasibility, and avoiding financially reckless entrepreneurship.”

“Analytics candidate with hands-on experience turning messy pricing and competitor data into reporting-ready SQL tables, plus building Python automation workflows that replaced manual processing across 40,000 images at roughly 89% accuracy. They also led a price elasticity analysis that informed differentiated pricing strategies and supported reporting through Power BI dashboards.”

“VR/social platform engineer with experience at AltspaceVR, Mozilla Hubs, and Dopple, spanning Unity/C#, custom engine networking, and early voice-agent systems. Particularly compelling for roles at the intersection of multiplayer, XR, and AI: they’ve built data-driven avatar systems, ownership-based netcode, VR replay capture, and a custom real-time voice->LLM->voice stack integrated with hardware and computer vision.”

“Built and deployed an AI-powered insurance claims fraud platform end-to-end using Java/Spring Boot, Kafka, OpenAI, pgvector, and AWS EKS. Stands out for combining LLM/RAG architecture with production-grade scalability and observability, delivering measurable impact including 62% less manual review, 40% better fraud precision, 37% higher throughput, and 99.95% uptime.”

“Senior software engineer with hands-on experience leading multi-agent AI workflows in financial trading infrastructure. Most notably, they applied a specialized agent setup on a high-frequency trading backend to cut delivery time from three weeks to ten days while improving validation against risk, performance, and compliance requirements.”

“Built end-to-end financial workflow platforms at Citi spanning React frontends, Spring Boot microservices, Kafka, Redis, and Oracle. Particularly compelling for teams needing someone who can modernize legacy systems into real-time architectures—the candidate cites a 48x throughput improvement from a batch-to-Kafka modernization effort.”

Javon Lee

Screened

Senior Software Engineer specializing in AI platforms and cloud-native systems

Baltimore, MD8y exp

“Engineer with startup CTO experience and recent hands-on full-stack work at Microsoft and Clarity, focused on compliance and AML workflow platforms for financial services. Stands out for building scalable data and audit systems that reduced manual processing and improved performance, while operating effectively in ambiguous early-stage environments.”

“Backend engineer with Citigroup experience who built and evolved a self-service user provisioning/identity backend, cutting onboarding from 45 minutes to under 2 minutes. Demonstrates strong production-grade integration and reliability practices (isolated integrations, retries, rollback logic, heavy logging) plus secure API development in Python/FastAPI with OAuth scope-based authorization and incremental, low-risk rollout strategies.”

“Built and owned Prism, a real-time collaborative coding platform, making key architectural choices around deterministic event ordering and a backend source-of-truth to improve trust under concurrent edits. Also created a Python-based bug analysis and test automation suite that became part of standard engineering workflow, cutting debugging time by ~95% while improving fault detection coverage.”

“Full-stack developer (Energywell) who led an internal admin dashboard end-to-end using React/Redux and a Go microservice, emphasizing performance (reduced calls, preload data) and maintainable architecture (modularity, refactoring, PR reviews). Also shipped a Redis-based caching whitelist feature in a fast-paced environment and helped implement a responsive, brand-configurable onboarding/signup frontend.”

“Built and productionized an NLP-powered customer support assistant at JPMorgan Chase for digital banking, focused on reducing response time for repetitive client queries. Strong in real-world AI deployment challenges—sensitive data handling, low-latency FastAPI services, and AWS/Kubernetes operations with CI/CD—plus a metrics- and guardrails-driven approach to reliable AI workflows.”

“Engineering leader who proposed and delivered a new API-based document management platform to replace a vendor-dependent system, improving latency by ~1s and availability to 99.9% while migrating legacy data. Also drove Python-based automation of ~12 workflows via third-party API integrations and led an SSO/auth integration focused on backward compatibility and high login success rates.”

“Founding engineer for an AI product (“world’s first funny AI”) who designed and implemented the full-stack architecture (React/TypeScript + Node) and migrated production from Vercel to AWS. Shipped a Lambda-based image pipeline that eliminated lag/missing images and brought page load times to under a second, and has hands-on experience integrating multiple LLM providers (OpenAI, Claude, Gemini, Grok) with structured-output and self-check reliability techniques.”

“QA automation engineer with experience at Amazon Game Studios owning an end-to-end automated scale testing suite that simulates high-concurrency gameplay and captures performance telemetry. Improved coverage by bypassing hours of gameplay via programmatic state setup, enabling repeatable 4000-player dungeon-entry tests that exposed a messaging-queue bottleneck fixed before release. Also built maintainable Selenium/pytest UI automation with CI gating, reporting, and flake-reduction patterns.”

“Engineering leader/player-coach who led a high-stakes 0→1 in-house usage-based billing/rating platform to replace a third-party system, saving millions and protecting 30M+ in revenue. Deep experience in event-driven microservices on AWS (Lambda/SQS/DynamoDB), billing correctness, migrations, and incident response, while scaling teams through hiring, coaching, and lightweight execution processes.”