Vetted Prometheus Professionals

Pre-screened and vetted.

BH

Senior Full-Stack Engineer specializing in AI/GenAI and cloud-native platforms

Dallas, TX13y exp
Kamet Consulting GroupUniversity of Texas at Austin
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RY

Mid-level Full-Stack Python Developer specializing in cloud-native platforms and payments

California, USA6y exp
AmazonConcordia University Wisconsin
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AS

Mid-level Software Engineer specializing in real-time backend systems and FinTech payments

San Francisco, CA6y exp
StripeWebster University
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JL

Senior Software Engineer specializing in Python, cloud microservices, and conversational AI

Chapel Hill, NC11y exp
GoogleUniversity of North Carolina at Chapel Hill
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JL

Executive AI Architect specializing in enterprise GenAI and LLM platforms

18y exp
Cogrithm.comUniversity of Colorado Boulder
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RC

Senior AI/ML Engineer specializing in computer vision, NLP, and real-time forecasting

Newark, CA10y exp
OutlierUC Berkeley
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JS

Senior Full-Stack Engineer specializing in FinTech and fraud/risk systems

Austin, TX11y exp
RampLehigh University
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TM

Senior Software Engineer specializing in cloud platforms for healthcare and e-commerce

San Jose, CA11y exp
AmazonGeorgia Tech
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FZ

Junior Software Engineer specializing in observability and cloud infrastructure

2y exp
FastlyUC Berkeley
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SY

Mid-level AI/ML Engineer specializing in LLMs, multimodal systems, and MLOps

5y exp
MetaEast Texas A&M University
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MT

Senior Software Engineer specializing in cloud platforms, data pipelines, and ML

Seattle, WA6y exp
MicrosoftMcMaster University
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GW

Senior AI Engineer specializing in Agentic AI and MLOps

Austin, TX11y exp
NomNomDataUniversity of Birmingham
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SS

Principal AI Infrastructure Engineer specializing in distributed systems and streaming platforms

San Francisco, CA13y exp
SplunkUC Berkeley
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KW

Senior Software Engineer specializing in AI-powered healthcare and distributed systems

Fort Lee, NJ10y exp
AmazonUniversity of Florida
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MM

Senior Software Engineer specializing in data platforms, APIs, and healthcare systems

9y exp
Broad Institute of MIT and HarvardUniversity of Oxford
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MS

Mujahid Shaik

Screened ReferencesStrong rec.

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

Ohio, USA5y exp
xAIKennesaw State University

Senior full-stack engineer with 5 years of experience across Bank of America, AT&T, and NextAI/XAI, building cloud-native, high-availability products spanning React, Node, Java, Kotlin, Python, and AWS. Particularly compelling for teams needing someone who can own architecture, implementation, DevOps, and UX polish end-to-end—from a real-time loan eligibility platform handling 50,000+ daily requests to live event dashboards that improved operations and helped drive $250K in ARR.

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AD

Anirudha Deo

Screened

Senior Engineering Manager specializing in cloud-native e-commerce and payments platforms

San Jose, CA23y exp
GoogleNagpur University

Senior Engineering Manager with large-scale platform/API ownership at eBay, leading a globally distributed team and redesigning Order public APIs used by external developer ecosystems at ~800M requests/day, delivering 84% performance gains and reducing compute by ~300 VMs. Also led Google CRES ETL migration work on GCP, creating reusable Python libraries to standardize configuration across 10 integrations and improve developer productivity.

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CK

Senior Backend Engineer specializing in Node.js, Java, and regulated SaaS platforms

Seattle, WA11y exp
MpathicBrown University

Built a production LLM-powered root cause analysis agent for supply chain alerts that helped operations managers avoid manual dashboard investigation. Demonstrates unusually strong depth in agent reliability, orchestration, and observability, with concrete production practices like hallucination blocking, shadow testing on 500 cases, and data-driven improvements that raised user agreement to 94% while cutting GPT-4 usage by 60%.

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KH

Kishan H

Screened

Senior Full-Stack Engineer specializing in Java microservices and cloud-native platforms

San Jose, CA5y exp
WalmartSaint Louis University

Backend-focused engineer with Walmart Global Tech experience building shipment and seller workflow systems using Spring Boot, GraphQL, Kafka, and async processing. Stands out for improving bulk label API performance by 60-75%, designing item-level partial-failure workflows that improved user clarity, and also exploring AI-powered debugging/RCA platforms with Java, Python, LangChain, and LLM integrations.

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fritzie alex - Executive engineering leader specializing in AI-native transformation and cloud modernization in San Francisco, CA

fritzie alex

Screened

Executive engineering leader specializing in AI-native transformation and cloud modernization

San Francisco, CA20y exp
AmazonDayananda Sagar College of Engineering

Senior software engineering leader who owned the architecture and delivery of a major VerizonWireless.com transformation, migrating an ATG monolith to Spring Boot/Java microservices with an event-driven architecture across 13 domains. Combines hands-on system design depth with business-facing architecture leadership and team scaling in complex enterprise environments.

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AM

Akhil Maram

Screened

Senior Data Engineer specializing in real-time data platforms and lakehouse architectures

Parker, CO8y exp
AirbnbLindsey Wilson College

Senior, product-focused engineer who has built real-time customer-facing web applications and a microservices backend (TypeScript/React/Node) using RabbitMQ, MongoDB, and Redis. Demonstrates strong operational maturity (idempotency, tracing/observability, backpressure) and built an internal console that became the primary tool for debugging, replaying jobs, and managing system behavior.

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SA

Shiva Arcot

Screened

Director of Security & Data Platform Engineering specializing in AI-driven cloud security

Sunnyvale, CA24y exp
ProofpointSanta Clara University

Player-coach engineering leader focused on scalable data security scanning and risk detection in hybrid cloud, owning architecture and core implementation of an incremental/parallel DSPM scanning engine. Shipped production improvements including 60% lower scan latency and 30% fewer false positives, with strong emphasis on correctness under concurrency, multi-tenant observability (SLOs/burn-rate alerts), and disciplined rollout practices (feature flags, shadow scans, canaries).

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