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Vetted Event-Driven Architecture Professionals

Pre-screened and vetted.

EW

Entry-Level Software Development Engineer specializing in AWS serverless and distributed systems

Sunnyvale, CA1y exp
AmazonUSC
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JD

Mid-Level Software Engineer specializing in distributed systems and AI agent platforms

Redmond, WA3y exp
MicrosoftSan Jose State University
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MC

Senior Software Engineer specializing in scalable backend systems and full-stack web apps

Austin, TX11y exp
IndeedCarnegie Mellon University
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LZ

Senior Software Engineer specializing in AI workflow orchestration and distributed systems

Foster City, CA10y exp
Relay.appUniversity of Pittsburgh
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GD

Senior Full-Stack Engineer specializing in Healthcare and FinTech platforms

Minnetonka, MN9y exp
UnitedHealth GroupPrinceton University
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HP

Mid-level Machine Learning Engineer specializing in LLMs, RAG, and GPU-accelerated cloud systems

Santa Clara, CA4y exp
NVIDIAConcordia University Wisconsin
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EC

Staff Full-Stack Software Engineer specializing in scalable web platforms and cloud infrastructure

San Francisco, CA12y exp
GustoCal Poly Pomona
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SU

Mid-level Full-Stack Developer specializing in React, Spring Boot, and AWS

6y exp
AmazonUniversity of North Texas
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AK

Mid-level Full-Stack Software Engineer specializing in data-intensive web platforms

Burlingame, CA5y exp
CalicoUC Santa Barbara
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JC

Mid-level Full-Stack Software Engineer specializing in distributed systems and GenAI platforms

Seattle, WA5y exp
AmazonSan Francisco State University
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DZ

Senior Backend Engineer specializing in Healthcare & Cloud Platforms

New York, NY11y exp
DeloitteColumbia University
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ML

Senior Software Engineer specializing in full-stack platforms, MLOps, and LLM search

Foreman, Arkansas10y exp
IQVIAUniversity of Florida
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JS

Senior Data Engineer specializing in cloud data platforms and real-time analytics

Remote10y exp
Scout MotorsUniversity of Texas at Austin
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VN

Mid-level Software Engineer specializing in backend systems, billing, and real-time data pipelines

CA, USA6y exp
StripeSoutheast Missouri State University
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RT

Rhutwij Tulankar

Screened ReferencesStrong rec.

Engineering Manager and ML/Data Architect specializing in scalable data platforms and personalization

San Francisco, CA11y exp
RecruiticsRochester Institute of Technology

Hands-on engineering manager at a marketing company leading a highly senior, distributed team (10 direct reports) while personally coding ~60–70% and owning end-to-end architecture across three interconnected products. Built agentic CRM automation and a reinforcement-learning-driven distribution layer for channel spend/bidding, with a strong focus on scalable design and observability (Prometheus/APM/logging) enabling frequent releases and few production incidents.

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VB

Vigynesh Bhatt

Screened ReferencesStrong rec.

Mid-level Software Engineer specializing in backend, cloud, and ML systems

Salt Lake City, UT4y exp
Goldman SachsBrigham Young University

Software engineer with experience across Goldman Sachs, BYU Broadcasting, Juniper Networks, and an edtech startup (Doubtnut), spanning data migrations, AWS-based media backends, and microservices observability. Built a Redis/ElastiCache caching layer in front of DynamoDB/S3 to improve media delivery latency and cost, and created an SEO indexing automation tool using the Google Search Console API that saved ~15–30 person-hours per day.

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AC

Director of AI/ML Engineering specializing in MLOps, data platforms, and 3D computer vision

Teaneck, NJ10y exp
AetrexColumbia University

Backend/data engineer focused on production ML/LLM systems: built a real-time FastAPI inference API on Kubernetes with strong reliability patterns (timeouts, idempotent retries, centralized error handling). Delivered AWS platforms using EKS + Lambda with GitHub Actions/Helm CI/CD and built Glue-based ETL from S3/Kafka into Snowflake with schema evolution and data-quality controls; also modernized legacy analytics/recommendation workflows into Python services with safe, feature-flagged cutovers.

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DJ

Dimple Joseph

Screened

Director of Engineering specializing in cloud-native SaaS, e-commerce search, and AI personalization

Redwood Shores, CA25y exp
OracleThe University of Texas at Arlington

Engineering leader (12+ years Director, 17 years lead) focused on developer productivity and platform/framework work across Oracle, PlayStation, Workday, and CafePress. Notable for building distributed teams from scratch and delivering high-impact platform architecture—e.g., re-architected PlayStation’s upload pipeline to support 500GB–5TB submissions using browser-to-AWS chunked uploads with SNS/SQS and deduplication/resume support.

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GK

Mid-level AI/ML Engineer specializing in LLMs, RAG, and multimodal deep learning

San Francisco, CA5y exp
MetaUniversity of Central Missouri

ML/LLM engineer who has built and productionized a large multimodal LLM pipeline end-to-end—fine-tuning a 20B+ parameter model with distributed/FSDP training and deploying on Kubernetes via Triton for ~5x throughput. Strong focus on reliability and safety (monitoring with SHAP, guardrails, A/B testing) with reported ~22% relevance lift and reduced harmful/incorrect outputs, plus experience orchestrating ETL/retraining workflows with Airflow across S3/Snowflake/RDS.

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RS

Rakshak Shah

Screened

Intern Software Engineer specializing in cloud, AI, and systems programming

Seattle, WA1y exp
AmazonUniversity of Michigan

AWS intern who significantly evolved a Drift Audit Service backend (Control Tower/EventBridge context) to make drift findings more explainable and reduce false positives by adding a verification step in Lambda before event ingestion. Demonstrates strong API design fundamentals in Python/FastAPI (contracts, idempotency, security controls) and careful rollout practices (feature flags, canaries, phased deployments).

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KS

Mid-Level Software Engineer specializing in event-driven FinTech backend systems

San Francisco, CA5y exp
StripeUniversity of Central Missouri

Backend/data-platform engineer with Stripe and Salesforce experience focused on global payouts/treasury systems. Built an end-to-end payout settlement monitoring platform (FastAPI microservices, Kafka/Spark streaming, React dashboard, CloudWatch alerting) that cut settlement delays 25% and reconciliation time 30%, and productionized an ML anomaly detection service that reduced missed issues by 30%. Experienced modernizing monoliths into microservices with feature flags/canaries and close partnership with treasury/risk/CTO stakeholders.

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