Vetted Authentication Professionals

“Developer with a pragmatic, disciplined approach to AI-assisted coding: uses tools like Copilot, ChatGPT, and Gemini to speed up debugging, optimization, unit testing, and documentation while maintaining ownership of design and code quality. Interested in expanding from single-agent workflows into multi-agent setups for larger coding tasks and stays current through hands-on use and AI ecosystem updates.”

Brent Cook

Screened

Director-level product leader specializing in AI-powered search and discovery

Seattle, WA21y exp

“Former high school teacher turned product leader with deep experience in EdTech, scholarly search/discovery, and mobile content platforms. They’ve led complex end-to-end launches, including a direct-to-consumer app storefront delivered on a 7-month timeline and AI-powered research discovery features for a 5-billion-record search platform, while bringing a strong human-centered, accessibility-first perspective to AI products.”

MohmmadHussain Syed

Screened

Mid-level Full-Stack Engineer specializing in customer-facing web platforms

USA4y exp

“Full-stack product builder who described owning an AI-powered journaling platform end to end using React/Vue, FastAPI, Supabase, PostgreSQL, and Hugging Face APIs. Also shipped a customer-facing document upload feature for First National Bank by solving micro frontend integration issues with web components, and has built internal tooling such as a GitHub PR review app.”

“Backend-leaning full-stack engineer who has shipped real-time, customer-facing dashboards and ticketing/payment features at Freshworks and Global Payments. Strong in Python API design (Django/Flask/FastAPI) and React/TypeScript UIs, with hands-on experience scaling PostgreSQL for high transaction volumes and operating services on AWS, including incident response and HIPAA-aligned security controls.”

“Dell engineer with hands-on full-stack and AI-powered internal platform experience, spanning React/TypeScript frontends, Spring Boot/Python microservices, Kafka streaming, and AWS/Kubernetes deployment. They’ve owned monitoring and anomaly-detection products end to end, including a dashboard that reduced manual log review and helped teams detect issues roughly 30% faster, while also translating complex AI outputs into intuitive experiences for non-technical users.”

“Frontend engineer with experience at US Bank and S&P Global building complex React dashboards for analysts working with real-time, high-volume transaction and model-performance data. Stands out for combining performance tuning, scalable state architecture, and usability improvements that directly reduced manual analysis effort for expert users.”

“Frontend engineer focused on marketing and analytics products, including a real-time multi-touch attribution dashboard. Uses Next.js (SSR/ISR) with React/TypeScript and Tailwind, and emphasizes quality at scale via automated testing, CI/CD (GitHub Actions), feature-flagged staged rollouts, and Mixpanel-driven iteration. Experienced modern state management patterns (React Query + Zustand) and performance tuning (code-splitting, dynamic imports, lazy loading).”

“Full-stack engineer with experience at Vanguard, PNC, and Humana building customer-facing investment/banking flows and internal ops tools using Angular/React/TypeScript with Spring Boot microservices. Strong in shipping time-sensitive changes safely via automated testing/CI (JUnit/Mockito, Jenkins, SonarQube) and in operating event-driven microservices with Kafka (idempotency, retries, correlation IDs). Improved internal tool adoption by responding to ops/support feedback with query optimization and clearer search results.”

“Worked at easybee ai building a production-grade "voice of the customer" LLM intake agent, hardening a fragile sandbox prototype with JSON-schema constrained outputs, Python/FastAPI validation middleware, and automated retries. Strong in real-time debugging of agentic workflows (snapshot isolation, modular tracing) and in implementing safety/compliance guardrails like a content-moderation middleware to support enterprise adoption.”

“Solo-built and launched an AI logo generator SaaS in ~2 months using React/Next.js/TypeScript with managed auth and payments, deploying via Vercel/GitHub CI/CD. Also has hands-on AWS production experience running containerized services with Terraform-managed multi-environment infrastructure and strong reliability patterns for integrations/pipelines.”

“Backend-leaning product engineer with DevSecOps depth who has shipped real-time, Kafka-driven data pipelines and AI-enabled customer-facing features to production on AWS. Built a Spring Boot API layer serving real-time predictions at 100K+ requests/day, improving latency by 35% and user task completion by ~25%, and delivered a React/TypeScript dashboard plus a Postgres audit/history model optimized for search and large event volumes.”

Sai Kondapaka

Screened

Mid-Level Software Engineer specializing in microservices, data pipelines, and FinTech fraud detection

Remote, USA5y exp

“Backend engineer with PayPal experience owning a high-throughput, low-latency fraud detection pipeline processing billions of transactions/day, integrating LLM-based models into real-time Kafka streams and payment decisioning APIs. Strong Kubernetes + GitOps practitioner (declarative, auditable deployments; autoscaling/probe tuning) with migration experience modernizing legacy systems onto AKS/OpenShift.”

Sanket Dumbare

Screened

Mid-Level Software Engineer specializing in cloud-native microservices and FinTech platforms

USA3y exp

“Backend/platform engineer who led an end-to-end Python (FastAPI) transaction analytics microservice for real-time financial monitoring, including SQS ingestion, scoring/aggregation, and low-latency APIs. Strong AWS + Kubernetes/GitOps background (EKS, ArgoCD, Jenkins, ECS/ECR, CloudWatch) with hands-on experience scaling event-driven systems and executing phased on-prem to AWS migrations.”

Ivan Kadyka

Screened

Staff Technical Lead specializing in Unity and .NET

Warsaw, Poland11y exp

“Unity/gameplay engineer (Playtika) who built a state-machine/ECS-driven slot/bonus engine in a client-server setup, focusing on consistent outcomes under latency and highly engaging reward sequences. Also implemented server-authoritative real-time challenges/contests via an event-driven messaging system (SignalR-like) across iOS/Android/WebGL/UWP, and validates impact through retention/session/engagement analytics.”

Aravind Mohan

Screened

Junior Software Engineer specializing in AI agents and backend systems

Seattle, WA5y exp

“Backend/AI workflow engineer who built a production event-personalization service (FastAPI + AWS Lambda) and solved real-world reliability/latency issues with deterministic routing, caching, and query/index optimization. Also built an end-to-end Gmail-based job application tracking agent using a lightweight RAG pipeline with Gemini, strong guardrails (Pydantic schemas, confidence thresholds), and offline regression tests to prevent drift and hallucination-driven data corruption.”

“Backend/full-stack engineer with Blue Cross Blue Shield experience building a reactive, event-driven claims processing microservice platform on AWS (ECS, SNS/SQS) with Terraform-based IaC and strong observability (Dynatrace/CloudWatch). Demonstrated measurable production impact (32% less downtime, 24% higher processing efficiency) and deep database performance/migration expertise across MongoDB and Postgres.”

Ajay Desai

Screened

Mid-level Full-Stack Software Engineer specializing in FinTech and backend platforms

USA4y exp

“Built an AI-native legal research platform that automated analysis across 100,000+ dense legal documents, combining LLM workflows, async backend architecture, and conversational retrieval in production. Also brings cross-domain experience in investment-analysis agents and healthcare claims/billing systems, with a strong emphasis on reliability, deterministic orchestration, and safe handling of messy operational data.”

“Full stack Python developer who actively integrates AI coding assistants into day-to-day engineering work, including code generation, debugging, testing, and documentation. Has also coordinated multi-agent workflows across backend, frontend, testing, and code review, showing an applied, productivity-focused approach to AI-enabled software delivery.”

“Engineer focused on AI-assisted and multi-agent software development, with hands-on experience designing structured agent workflows for implementation, testing, validation, and architectural review. Stands out for treating AI as an accelerator rather than a replacement, combining practical experimentation with strong attention to engineering fundamentals and operational concerns like observability, latency, and cost.”

Sanket Mungikar

Screened

Mid-level Software Engineer specializing in distributed backend and AI analytics platforms

California, USA4y exp

“Full-stack engineer at BigCommerce who combines customer-facing deployment ownership with hands-on AI/LLM systems work. Built and launched merchant analytics and predictive inventory workflows using React, TypeScript, FastAPI, Kafka, AWS, and RAG-style architectures, and has real production experience debugging non-deterministic AI issues caused by data pipeline freshness and event-ordering problems.”

“Entry-level software engineer with strong full-stack experience building React/TypeScript and Node.js analytics products, especially around performance optimization for large datasets. Stands out for combining hands-on engineering with user discovery, and for delivering measurable wins like 40% fewer API calls, page load improvements from 3.2s to 1.1s, and 70% faster PostgreSQL queries during an internship at Tapastry.”

“Frontend-focused candidate with hands-on experience building React and TypeScript dashboards for searching, filtering, and analyzing large datasets in real time. Demonstrates practical performance tuning skills using React DevTools, memoization, debouncing, and pagination, and has also built a Mapbox-based location data dashboard with interactive markers and popups.”

“Full-stack product engineer who has built both operational systems and enterprise AI copilots in production. They owned an AI-powered inventory platform end-to-end, driving a 45% drop in stock issues, and also shipped a Microsoft Teams-based HR/IT copilot using RAG and workflow automation that reduced repetitive support queries by roughly 30%.”

“Built an internal AI-powered document search and Q&A platform at BNY that let employees query company documents in natural language and get grounded answers in seconds. Brings practical full-stack and LLM systems experience across React/TypeScript, FastAPI, Pinecone, OpenAI, and Claude, with clear emphasis on retrieval quality, hallucination reduction, and production monitoring.”