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Vetted Firebase Professionals

Pre-screened and vetted.

JN

Staff Software Engineer specializing in scalable backend systems and observability

Milan, MI14y exp
UnitedHealth GroupMichigan Technological University
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SW

Mid-Level Full-Stack Software Engineer specializing in web platforms and AWS

3y exp
AmazonUniversity of Illinois Urbana-Champaign
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VA

Staff Full-Stack & AI Engineer specializing in LLM agents, RAG, and cloud-native systems

Plano, TX11y exp
UpboundSonoma State University
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RC

Staff Software Engineer specializing in frontend platforms and healthcare UX

Houston, TX9y exp
TwilioUniversity of Houston
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ML

Staff Software Engineer specializing in cloud-native distributed systems for healthcare

Redding, CA11y exp
HumanaUC Davis
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SS

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

Remote, USA4y exp
Capital OneIllinois Institute of Technology
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AB

Mid-level AI Engineer specializing in LLM agents and RAG on Azure

Chicago, IL3y exp
Northern TrustGeorgia Tech
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RC

Technology Executive specializing in AI-native engineering and cybersecurity governance

Remote, VA17y exp
Cyber FoundryFresno State
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DL

Staff Software Engineer specializing in enterprise SaaS, AI assistants, and distributed systems

Houston, TX12y exp
GleanUniversity of Texas at Austin
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MM

Executive Digital & Engineering Leader specializing in D2C omnichannel and AI transformations

Beverly Hills, CA18y exp
Alo YogaUniversity of Miami
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KG

Senior Full-Stack Software Engineer specializing in SaaS, cloud, and AI/LLM applications

11y exp
StealthStanford University
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SW

Mid-Level Frontend Software Engineer specializing in React and React Native

Taipei, Taiwan2y exp
ASUSGeorgia Tech
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SS

Mid-level Full-Stack Software Engineer specializing in AWS microservices and web platforms

Seattle, WA3y exp
AmazonUniversity of Central Florida
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ML

Senior Technical Game Designer specializing in AI, combat systems, and VR

Burnaby, Canada10y exp
MetaCentre for Digital Media
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VS

Junior Software Engineer specializing in full-stack development and applied ML

New York, NY2y exp
AmazonNYU

Full-stack engineer with experience at Zoho and Amazon who has owned production systems end-to-end, including a monolith-to-microservices migration using Kafka and Cassandra that improved search latency ~25% and increased throughput without data loss. Also built a hackathon project (Buildwise) into a sold product for a construction company (AI-driven document compliance checks) and shipped an IoT-based parking availability MVP in 3 weeks.

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GW

Geng Wang

Screened

Staff Product/UX Designer specializing in enterprise platforms, data visualization, and AI interfaces

San Jose, CA26y exp
VariousIndiana University

UX/product designer with deep healthcare and mission-critical software experience across 3M Healthcare, GE Healthcare, and Motorola. Has designed complex lab automation and radiology workflows end-to-end, combining rigorous field research with hands-on engineering (HTML/CSS/TypeScript/React, Storybook) and even building live prototypes (Firebase + Angular) and production-ready UI control libraries to ship.

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SS

Shuju Sun

Screened

Mid-Level Software Engineer specializing in real-time data pipelines and ML deployment

PA, USA4y exp
VanguardUSC

Ticketmaster data engineer who built CDC-driven Kafka pipelines feeding Snowflake for analytics and data science teams. Hands-on in production operations—scaled Kafka during sudden playoff-driven transaction spikes and improved monitoring for preemptive scaling. Known for using small-batch experiments and quantitative metrics to align stakeholders and drive cost-saving architecture changes (e.g., buffering to reduce AWS Lambda invocation frequency).

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WL

winston lo

Screened

Junior Software Engineer specializing in AI agents, RAG, and full-stack development

Remote2y exp
Tresle AIUC Berkeley

Backend engineer who built and iterated a secure, multi-tenant RAG system over a large document corpus, emphasizing strict RBAC/ACL isolation, hybrid retrieval (vector+keyword), reranking, and strong observability to balance relevance, latency, and cost. Also led production refactors/migrations using strangler + feature flags/dual writes and has experience catching subtle real-world failure modes (including in a sensor calibration optimization pipeline).

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SS

Shubham Singh

Screened

Mid-level Software Engineer specializing in LLM systems and intelligent search

CO, USA6y exp
PalantirSan José State University

Backend engineer from Palantir who built and productionized an enterprise LLM-based document intelligence/search platform, evolving it into a hybrid lexical+vector retrieval system. Emphasizes reliability and cost control via strict LLM gating, robust fallback paths, and evaluation frameworks (e.g., MMLU/BLEU), plus disciplined migration practices (feature flags, dual-writes, shadow reads) to ship changes safely at scale.

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SS

Shubham Singh

Screened

Mid-level AI/ML Engineer specializing in speech, computer vision, and agentic GenAI

Pittsburgh, PA6y exp
Musing AICarnegie Mellon University

Built and shipped a production multi-agent, voice-based conversational assistant for older adults’ daily health management using Vertex AI, FastAPI, Firebase/Firestore, and Cloud Run, with a custom cross-session memory design to keep responses context-aware at low latency. Also partnered with caregivers/elderly users and health officials, translating needs into workflows and explaining HIV risk predictions with SHAP and dashboards.

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TJ

Senior Full-Stack Software Engineer specializing in FinTech payments and fraud systems

Plano, TX8y exp
AffirmTexas Tech University

Backend/data engineer with production experience building credit/fraud enrichment services and checkout pipelines on AWS (EKS + Lambda) using FastAPI, Kafka, Postgres, and Redis, with a strong focus on reliability patterns (timeouts/retries/circuit breakers) and observability. Has also built AWS Glue/PySpark ETL into S3/Redshift with schema evolution and data quality controls, and modernized legacy credit decisioning into Java/Node microservices with parallel-run parity validation and feature-flag rollouts.

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