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Vetted TypeScript Professionals

Pre-screened and vetted.

ML

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

Foreman, Arkansas10y exp
IQVIAUniversity of Florida
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TA

Senior DevSecOps Engineer specializing in secure cloud CI/CD and compliance automation

Santa Clara, CA6y exp
ServiceNowUniversity of Antelope Valley
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NT

Mid-Level Full-Stack Software Engineer specializing in cloud-native systems and FinTech

CA, USA5y exp
MetaCalifornia State University, Sacramento
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RP

Junior Frontend Software Engineer specializing in React, TypeScript, and performance optimization

Chicago, IL3y exp
UberIllinois Institute of Technology
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XD

Junior AI Software Engineer specializing in LLM systems and retrieval (RAG)

Austin, Texas1y exp
CDK GlobalUniversity of Texas at Austin
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PD

Senior Software Engineer specializing in AWS distributed systems and developer tools

Santa Clara, California9y exp
Amazon Web ServicesUniversity of Massachusetts
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GP

Junior Robotics Test Engineer specializing in ROS2 autonomous mobile manipulation

Fremont, CA1y exp
Anyware RoboticsUC Berkeley
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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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SS

Intern Full-Stack Software Engineer specializing in distributed systems and cloud services

1y exp
AmazonDuke University
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YP

Senior Full-Stack & AI/ML Engineer specializing in FinTech and Healthcare IT

Remote12y exp
SnykUC Berkeley
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AA

Principal Data Scientist / AI Engineer specializing in healthcare-native AI platforms

New York, NY12y exp
Komodo HealthLewis University
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OA

Junior Software Development Engineer specializing in AWS automation and data pipelines

Toronto, ON1y exp
Amazon
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SI

Staff-level Software Engineer specializing in Unity game development and AI integration

London, UK9y exp
Meta
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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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OC

Senior Software Engineer specializing in developer tools, cloud automation, and generative AI

Redmond, WA13y exp
AmdocsUniversidad Autónoma de Guadalajara

Built and deployed a production chatbot on osvaldocalles.com and iterated through real-world LLM engineering issues: model quota/cost tradeoffs (migrating to Nova Pro), RAG accuracy via semantic chunking, AWS IAM/guardrail/security pitfalls, and Lambda/API Gateway streaming constraints (prefers JS for streaming layer). Experienced with agent orchestration using Strands SDK (AWS-focused) and LangGraph (Vercel/container deployments), plus evaluation pipelines using LLM-as-evaluator, dashboards, and staged model rollouts.

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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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YS

Yashvi Shah

Screened

Mid-Level Software Engineer specializing in distributed systems and cloud platforms

Sunnyvale, CA3y exp
AmazonUSC

Amazon Alexa engineer who architected and shipped a GenAI Knowledge Agent used by 2M+ customers, focused on making LLM outputs auditable via citations and a verification layer that prevents hallucinations. Built the full vertical slice (FastAPI/LangChain backend + React/TypeScript streaming UI) while keeping p99 latency under 200ms, and has proven incident response experience on AWS (Lambda/DynamoDB scaling issues).

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AS

Ashi Sinha

Screened

Junior Software Engineer specializing in full-stack and ML/NLP systems

New York City, NY2y exp
IBMUniversity of Massachusetts Amherst

Entry-level full-stack engineer with internship experience at Amazon (Appstore IAP flow + uninstall recommendation workflow) and a health-tech startup (OneVector) where they built a DSUR reporting workflow end-to-end, including document generation, S3-backed versioning/metadata, and secure preview/download. Demonstrates strong production debugging and reliability mindset (instrumentation, deterministic retrieval, idempotent writes) and focuses on UX/performance in high-stakes user flows.

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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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AA

Mid-level Software Engineer specializing in distributed systems and FinTech infrastructure

New York, NY
BloombergNYU

Early-career software engineer who owns revenue-critical invoice processing and internal ops tooling end-to-end. Has built TypeScript/React systems backed by MongoDB and Temporal, and designed scalable SQS-based onboarding workflows with FIFO/DLQ monitoring. Notably redesigned an Authzed SpiceDB authorization model, shrinking a 500+ line schema to ~20 lines while meeting sub-100ms p95 latency.

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SD

Shiting Ding

Screened

Mid-level Software Engineer specializing in Ads backend and ML infrastructure

Palo Alto, CA3y exp
AmazonUC San Diego

Customer-facing technical professional with Amazon incident-management experience who helps drive adoption of complex ML/LLM solutions by delivering hands-on demos and rapid model fine-tuning. Applies a disciplined debugging approach (repro + logs/metrics + severity triage) and maintains runbooks to resolve SEV2 issues in ~1 hour, while also partnering with sales/customer teams to ship patches and new features based on feedback.

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FG

Frank Goodman

Screened

Executive Engineering & Product Leader specializing in Cloud/SaaS observability and security

San Jose, CA31y exp
GigamonUC Berkeley

Product/technology leader with deep security and cloud infrastructure expertise who drove a major shift from hardware-based networking/security appliances to cloud-native capabilities, growing cloud revenue from $0 to $400M in 4.5 years. Led an innovative eBPF-based approach (“precryption”) to enable lightweight cloud TLS interception/decryption, and has hands-on coding interest (recent Rust work on a personal cybersecurity identity/trust platform).

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