Vetted Go Professionals

Pre-screened and vetted.

RC

Mid-level Software Engineer specializing in FinTech and AI platforms

USA5y exp
Morgan StanleyUniversity at Buffalo
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AG

Intern-level Software Engineer specializing in full-stack and cloud systems

Gainesville, FL3y exp
University of Florida College of MedicineUniversity of Florida
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SC

Senior Backend Engineer specializing in FinTech compliance systems

Irvine, CA11y exp
OrigenceUC Irvine
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AW

Senior Software Engineer specializing in compliance, FinTech, and healthcare platforms

Frisco, TX10y exp
DeloitteUniversity of North Texas
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BJ

Senior Full-Stack Software Engineer specializing in .NET enterprise web systems

Dallas, TX10y exp
Sage ITTexas Tech University
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LJ

Senior Full-Stack Engineer specializing in compliance, integrations, and data platforms

Houston, TX10y exp
HexagonVirginia State University
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RC

Senior Full-Stack Engineer specializing in Healthcare IT and FinTech

Houston, TX14y exp
FullStack LabsUniversity of Houston
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GY

Senior Full-Stack Engineer specializing in scalable backend and marketplace systems

San Francisco, CA11y exp
TaskRabbitUniversidad Tecnológica de Panamá
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SP

Mid-level DevOps & Platform Engineer specializing in Kubernetes and AWS infrastructure

La Jolla, CA6y exp
Altium
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AR

Mid-level Full-Stack Developer specializing in cloud-native microservices

Oregon, USA5y exp
Salesforce
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AM

Principal Automation Architect specializing in cloud DevOps, microservices, and MLOps

Spring, TX16y exp
SparkSoft
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AI

Senior DevOps/SRE Engineer specializing in multi-cloud infrastructure and Kubernetes

Chicago, IL11y exp
Northwestern Memorial Hospital
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AR

Aniruddha Rajnekar

Screened ReferencesModerate rec.

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

Raleigh, NC5y exp
NC State UniversityNorth Carolina State University

Full-stack engineer with about 3 years of experience who is deeply hands-on with AI-assisted development and agentic systems. Built TubeAgent using LangChain, Ollama, FAISS, and Llama 3, and has demonstrated measurable impact by cutting review time by 90% and reducing deployment time from 30 minutes to under 5 minutes at NC State. Combines practical experimentation with strong architectural thinking around resilient, composable AI systems.

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Bill Cheng - Director-level Engineering Leader specializing in SaaS platforms and AI systems in Remote, USA

Bill Cheng

Screened ReferencesStrong rec.

Director-level Engineering Leader specializing in SaaS platforms and AI systems

Remote, USA26y exp
Foreclosure Listing Deep AnalysisSouthern Illinois University Carbondale

Entrepreneurial candidate building an LLC focused on applying AI to improve call center customer service, with an early go-to-market focus on local government call centers. They are already in discussions with a government prospect and have a clear thesis around solving high turnover and low knowledge retention through AI-assisted training and support systems.

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MS

Mid-Level Software Engineer specializing in Cloud Infrastructure and Full-Stack Platforms

San Jose, CA6y exp
GembizzSan José State University

Built and shipped a production LLM-powered grading platform that automates rubric-aligned scoring and feedback, with strong guardrails (RAG grounding, structured JSON, validation/retries) and operational rigor (metrics, drift monitoring). Experienced using CrewAI to orchestrate multi-agent workflows end-to-end and validating quality via gold-set benchmarking against human graders with regression testing on every prompt/model change.

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CD

Mid-level DevOps & Cybersecurity Software Developer specializing in IAM/CIAM automation

Montreal, Canada11y exp
AtekoConcordia University

Frontend engineer who led the end-to-end UI for an internal employee catalog tool at Genetec, building React/TypeScript dashboards with complex search filters. Emphasizes tight product-owner feedback loops (weekly demos), Figma-based design alignment, and disciplined delivery practices using CI/CD, automated tests, and version tagging for rollouts/reverts.

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RK

Rajeev Kurra

Screened

Embedded Software Engineering Intern specializing in automotive embedded systems and DSP

Madison, WI2y exp
NavTech ElectronicsUniversity of Wisconsin–Madison

Robotics/embedded engineer who built core firmware for an autonomous underwater vehicle (AUV) used to detect wreckage in shallow coastal waters, including propulsion control, sonar/magnetometer processing, and low-frequency magnetic underwater comms. Demonstrated strong real-time systems skills by redesigning a noisy comms protocol (checksums/retries) and implementing a lightweight scheduler to stabilize heading control, plus ROS 2 sensor/control integration with tf2 and simulation/CI tooling.

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SS

Swapnil Surdi

Screened

Senior Full-Stack Software Engineer specializing in API architecture and AI agentic RAG systems

Los Angeles, CA8y exp
Treatment Technologies & InsightsUSC

Hands-on backend/AI engineer who solo-built two production Claude-based agent systems: an internal Slack RAG over Confluence/Jira/code/regulatory docs and a HIPAA/GDPR-compliant patient chatbot with embedding guardrails and expert-in-the-loop evals. Also architected a multi-region patient portal + microservices platform with Terraform/CI-CD and federated gateways, delivering major onboarding automation and strong reliability wins (PgBouncer, chaos/perf testing).

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AH

Junior Software Engineer specializing in backend systems and LLM/RAG applications

Remote, USA1y exp
Potters TechArizona State University

Full-stack engineer who built a cloud storage app feature (file upload/management) with Next.js App Router + TypeScript and owned post-launch improvements. Also has internship experience building a geospatial AI chatbot: designed Postgres/PostGIS data models and optimized spatial queries, and implemented an LLM workflow orchestrated with LangChain/LangGraph plus a RAG pipeline grounded in OpenStreetMap data to reduce hallucinations.

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RG

Mid-level Backend Python Engineer specializing in APIs, microservices, and data pipelines

USA, USA4y exp
Marsh McLennanFlorida Atlantic University

Backend engineer (Marsh McLennan) who evolved a high-volume claims automation pipeline in Python, emphasizing thin APIs with background job processing, strong validation/retries, and production-grade observability. Experienced in secure FastAPI API design (centralized JWT/RBAC), multi-tenant Postgres/Supabase-style row-level security, and low-risk refactors using parallel runs and feature flags; targeting founding-engineer scope roles.

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