Vetted High Availability Professionals

Pre-screened and vetted.

HI

Principal Software Engineer specializing in enterprise AI/ML and multi-cloud architecture

17y exp
Mayo ClinicCapitol Technology University
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BP

Executive Security & Enterprise Architecture Leader specializing in cloud, privacy, and M&A

24y exp
Capital OneUniversity of Maryland Global Campus
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VB

Mid-level Software Engineer specializing in backend systems and LLM applications

Chicago, IL4y exp
Easley-Dunn ProductionsUniversity of Illinois Urbana-Champaign
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RW

Executive technology and operations leader specializing in media and entertainment

Santa Clarita, CA22y exp
CYNRG Entertainment LLCPepperdine University
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VM

Mid-level Backend Engineer specializing in cloud and distributed systems

San Francisco, CA4y exp
SalesforceSaint Louis University
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PN

Mid-Level Software Engineer specializing in cloud-native microservices and AI automation

Irving, TX4y exp
UberOklahoma State University
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SL

Senior Full-Stack Engineer specializing in cloud microservices on AWS

6y exp
AmazonUniversity of Missouri-Kansas City
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SM

Senior Linux Systems Engineer specializing in Cloud, DevOps, and Kubernetes

New York, NY7y exp
TikTokUniversity of Sindh
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AM

Abhishikth Meesala

Screened ReferencesStrong rec.

Mid-level AI/ML Engineer specializing in NLP, Generative AI, and fraud detection

Dallas, TX4y exp
PwCCampbellsville University

At PwC, built and productionized an agentic RAG enterprise search assistant over 6M internal documents (8M embeddings), deployed across AWS and GCP. Drove major retrieval gains (72%→92% precision via BM25+dense hybrid with RRF and cross-encoder re-ranking), reduced hallucinations 30%, achieved <2s latency at 50–60K queries/month, and cut support tickets 30%—boosting adoption to 2,500 users by adding source-cited answers.

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HS

Haider Shah

Screened

Principal AI/ML Architect specializing in GenAI, LLMs, RAG, and Agentic AI

California, USA13y exp
PineconePreston University

FinTech/AI engineer who has shipped an end-to-end discrepancy-detection product for financial managers using Next.js, FastAPI/GraphQL, Pinecone, and AWS (with dev/staging/prod, observability, A/B testing, and documentation). Also built an AI-native “AI Genesis” system with agentic cyclic workflows, routing, and tool use, and has experience modernizing legacy systems via the strangler fig pattern while coordinating with senior stakeholders on a 5G autonomous simulation platform.

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Albert Ghunney - Executive engineering leader specializing in FinTech, payments, and cloud platforms in Raleigh, NC

Executive engineering leader specializing in FinTech, payments, and cloud platforms

Raleigh, NC16y exp
Juze TechnologiesDrexel University
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SK

Mid-level Full-Stack Developer specializing in Python, React, and cloud-native AI microservices

San Francisco, CA6y exp
ShopifySaint Louis University
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NK

Mid-level DevOps Engineer specializing in multi-cloud Kubernetes and CI/CD automation

Remote, USA5y exp
IntuitSouthern Arkansas University
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SN

Senior DevOps Engineer specializing in cloud-native CI/CD and Kubernetes

SanJose, CA9y exp
AcerJawaharlal Nehru Technological University
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VD

Senior Software Engineer specializing in backend systems and AI-driven automation

Bengaluru, India6y exp
Morgan StanleyUniversity at Buffalo
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VK

Mid-level Software Engineer specializing in backend systems and LLM-powered AI applications

San Francisco, CA6y exp
Twist BioscienceUniversity of Texas at Arlington
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DD

Senior Backend Software Engineer specializing in FinTech and Healthcare APIs

5y exp
Morgan StanleyUniversity at Buffalo
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VP

Mid-level Software Developer specializing in backend, cloud-native systems, and AI automation

Richardson, TX3y exp
Goldman SachsUniversity of Texas at Arlington
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HZ

Harvey Zhang

Screened ReferencesModerate rec.

Staff Platform Engineer specializing in healthcare systems and observability

Buffalo Grove, IL24y exp
CVS HealthNorthern Illinois University

Hands-on production engineer with deep Oracle tuning and observability-driven troubleshooting experience in a 24x7 healthcare system used by pharmacists across the U.S. While not yet hands-on with GCP databases, they bring strong transferable cloud and platform experience from AWS/Azure, including migration work, memory leak remediation, HA/DR operations, and end-to-end performance debugging across DB, JVM, and network layers.

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WG

William Genovese

Screened ReferencesModerate rec.

Executive IT & Quantum Computing Leader specializing in cybersecurity and enterprise transformation

34y exp
Cyber EagleWestern Connecticut State University

Chief Quantum Officer working at the intersection of quantum and AI, motivated by market opportunities to safely accelerate AI adoption. Four-time CIO/CTO with global technical and business leadership experience, plus exposure to the startup funding ecosystem through Newchip (Austin-based accelerator) and fund advisory work with AFG Partners in Hong Kong.

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MG

Senior AIX/Unix Infrastructure Engineer specializing in IBM Power and enterprise migrations

Hilliard, OH15y exp
American GreetingsBangalore University

AIX/Solaris and IBM Power specialist who has led real-time performance recoveries for core banking/ERP workloads—diagnosing CPU/IO contention down to FC queue depth and LPAR sizing, restoring latency from 5s to 200ms. Experienced with POWER7/8/9 operations across HMC/VIOS/NPIV and live DLPAR resizing, plus legacy Solaris SPARC to RHEL x86 hybrid re-platform migrations with post-cutover Oracle performance considerations.

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NK

NEHA KOLAN

Screened

Mid-Level Software Engineer specializing in microservices and cloud data pipelines

Texas, USA4y exp
CignaUniversity of North Texas

Full-stack engineer with end-to-end ownership across React/TypeScript frontends, Spring Boot/Node microservices, and production ops on Docker/Kubernetes and AWS (ECS/CloudWatch). Built real-time healthcare eligibility and analytics systems at Cigna and an early-stage seller onboarding platform at Flipkart, driving measurable performance gains (35–40% latency/throughput improvements) through event-driven Kafka pipelines, Redis caching, and strong reliability/observability practices.

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