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Vetted Confluence Professionals

Pre-screened and vetted.

SS

Saleem Sultan

Screened ReferencesStrong rec.

Director-level Product & Engineering Leader specializing in AI/ML, cloud platforms, and digital transformation

Dallas, TX10y exp
HCSCCornell University

Senior engineering/technology leader who has defined and delivered a multi-year roadmap to modernize platforms and embed AI, leading global teams through cloud-native and microservices migrations on AWS/Azure. Demonstrated measurable outcomes including 99.99% uptime, 40% fewer incidents, 25% faster delivery, 5x scalability, and $30M in new business opportunities, while scaling a 100+ person distributed org with strong OKR-driven execution and mentorship culture.

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JM

Mid-level AI/ML Engineer specializing in LLM fine-tuning, RAG, and scalable inference

Bay Area, CA5y exp
MetaSoutheast Missouri State University

ML/LLM engineer who built and shipped an LLM-powered internal knowledge assistant at Meta, focusing on production-grade RAG to reduce hallucinations and improve trust. Deep experience with scaling and serving (FSDP/DeepSpeed/LoRA, Triton, Kubernetes autoscaling) and reliability practices (Airflow retraining, MLflow versioning, monitoring with rollback), including sub-100ms latency and ~35% GPU memory reduction.

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DG

Mid-level Full-Stack Developer specializing in Java/Spring Boot and React

Seattle, WA5y exp
ShopifySaint Louis University

NVIDIA engineer who built and shipped a production LLM-powered enterprise knowledge system (summarization, transcription, and Q&A) that cut document retrieval time ~30%. Deep hands-on experience with RAG (FAISS/Pinecone), GPU-accelerated microservices on AWS, and reliability/safety practices (Guardrails AI, prompt A/B testing, canary releases) plus strong MLOps orchestration across Airflow, Step Functions, and Kubernetes GitOps.

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MB

Martin Bom

Screened

Director-level Engineering Leader specializing in cloud services and large-scale delivery

Amsterdam, Netherlands31y exp
AmazonAvant University of Applied Sciences

Engineering leader with a hands-on developer background who has launched and scaled cloud services at AWS (CloudShell) while also leading AWS Cloud9. Built multi-year roadmaps and cross-org stakeholder alignment (product/marketing/mobile), and has a track record of scaling teams (3x growth) by implementing operational excellence, automated quality gates, and security champion programs; advocates serverless architectures to minimize maintenance and accelerate global expansion.

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SM

Staff Full-Stack Engineer & System Architect specializing in distributed systems and microservices

South San Francisco, CA18y exp
Twist BioscienceUniversity of Colorado Boulder

Player-coach engineer/leader with experience at Twist Bioscience and Series B startup Vida Health, owning high-impact platform work across frontend and backend. Delivered a large-scale permissions migration to Okta affecting ~100,000 users and led reliability/process improvements (weekly releases, dedicated QA/dev environments, incident response with RCA) in high-growth environments.

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JC

Mid-level Game Producer / Feature Designer specializing in player-focused game development

Orlando, FL7y exp
MoonSpice GamesFlorida Interactive Entertainment Academy (FIEA), University of Central Florida
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MC

Staff Software Engineer specializing in Healthcare IT and mobile platforms

Berkeley, CA12y exp
AmazonSan Francisco State University
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SR

Senior AI/ML Engineer specializing in LLMs, RAG, and multimodal systems

San Francisco, CA7y exp
Scale AIConcordia University Wisconsin
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SS

Senior Machine Learning Engineer specializing in LLMs and scalable MLOps

San Francisco, CA7y exp
MetaIndiana University
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SB

Senior Full-Stack Software Engineer specializing in Java/Spring and modern web apps

Lanham, Maryland10y exp
GoogleUniversity of Buea
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SA

Executive Technology Leader specializing in SaaS platforms and Generative AI

San Francisco, CA18y exp
AmazonWharton School
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SM

Senior Python Backend Engineer specializing in cloud-native SaaS and microservices

Spanish Fork, UT11y exp
VercelUtah Valley University
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AY

Senior Corporate Development & Strategy professional specializing in M&A and product strategy

Washington, DC6y exp
CitigroupWharton School
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VK

Mid-level AI/ML Engineer specializing in LLMs, RAG, and scalable MLOps

Cupertino, CA5y exp
OpenAIUniversity of North Carolina at Charlotte
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AB

Mid-level Software Engineer specializing in backend APIs, data pipelines, and cloud microservices

CA, USA6y exp
NVIDIAConcordia University Wisconsin
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NV

Senior AI/ML Engineer specializing in LLM agents, RAG, and production ML systems

San Francisco, CA7y exp
OpenAISaint Louis University
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BT

Senior Cloud Engineer specializing in AWS/Azure infrastructure, DevOps, and cloud-native platforms

Remote10y exp
SnowflakeUniversity of Texas at Austin
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RG

Rodolfo Garcia

Screened ReferencesStrong rec.

Senior QA Test Analyst specializing in game and service testing

Los Angeles, CA11y exp
NetflixLos Angeles Mission College

Game QA/automation tester with experience at Blizzard, Bossfight Entertainment, and Netflix, spanning manual-to-automation transitions, Selenium/C# UI automation, and CI/CD nightly reporting via TestRail. Known for an end-user-driven test strategy, strong defect isolation (including crash dumps), and cross-functional test planning that influenced multiplayer UX/design decisions.

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PP

Entry-level Supply Chain & Test Engineer specializing in warehouse automation and robotics

1y exp
Procter & GambleMichigan State University

P&G operator who is also building and selling an AI receptionist (voice agent) SaaS for healthcare/service clinics, using EHR + calendar API compatibility to target accounts and letting the Voice AI run parts of the demo to prove value. Has already closed and deployed to two clients in the last two months, with production impact via reduced front-desk overhead and automated scheduling/FAQs, and brings a structured, scalable deployment/process mindset from global WMS rollouts.

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DO

Dan Olson

Screened

Director-level Product Operations & Program Management leader in consumer electronics

San Jose, CA27y exp
RokuWillamette University

Operations leader with Apple and Roku experience who owned founder-level, cross-functional initiatives including Roku’s Brazil market entry (regulatory, tax/entity setup, manufacturing/logistics, and launch metrics) with direct CEO oversight. Built Roku’s International Business Operations function from zero—standardizing OKRs, dashboards, and country-level P&Ls—and influenced major strategic decisions like exiting a ~$10.5M-loss UK channel business and restructuring Mexico ads go-to-market via partnership.

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JS

Senior Strategy & Analytics Lead specializing in AI, media, and sports analytics

6y exp
Scale AIMIT Sloan School of Management

Chief of Staff to the COO / Strategy & Business Development leader at Annapurna who unified four distinct entertainment verticals (film, TV, interactive, theatre) into the company’s first cross-functional five-year plan. Built standardized pipeline reporting, forecasting models grounded in real execution rates, and executive dashboards that improved decision-making speed and COO leverage while navigating creative/finance tension and sensitive information.

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RK

Mid-level Strategy & Consulting professional specializing in data-driven finance and analytics

Miami, FL5y exp
American ExpressUniversity of Michigan

BCG consultant with repeated "founder-level" ownership of large, cross-functional initiatives, including a financial services data management transformation delivering +30% client satisfaction and -60% issue resolution time. Also led portfolio strategy for a $160B biopharma client, building board-level models and aligning stakeholders across five segments to drive a 23% price increase and improved post-merger cost structure.

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SS

Mid-level Python Backend Developer specializing in cloud-native microservices and AI/ML platforms

USA4y exp
NVIDIASanta Clara University

Backend/AI engineer who built a production GPU-backed real-time inference API at Nvidia and debugged burst-induced tail latency, cutting P95 by ~29% through dynamic batching and backpressure. Also shipped an end-to-end RAG + agentic operational diagnostics assistant with strict tool controls, evidence citation, confidence gating, and strong production guardrails, plus demonstrated hands-on Postgres optimization (900ms to 40–60ms).

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