Vetted TypeScript Professionals

Pre-screened and vetted.

Shreya B - Mid-level Software Engineer specializing in backend, cloud-native, and GenAI systems in Redmond, WA

Shreya B

Screened

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

Redmond, WA5y exp
Quadrant TechnologiesUniversity of Cincinnati

Software engineer with strong Java/Spring Boot backend depth and hands-on full-stack experience building AI-powered enterprise knowledge assistants and customer-facing order tracking systems. Stands out for combining RAG/LLM product work, event-driven microservices, and user-trust-focused product iteration, including shipping prototypes that became the basis for broader production workflows.

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SA

Director-level GenAI product leader specializing in conversational AI and platform strategy

San Diego, CA18y exp
AmazonUniversity of North Carolina at Charlotte

Product leader with experience at Amazon and Temenos, focused on AI-powered consumer experiences at scale. They led critical Alexa+ launches, including the first Suno music-generation integration on Alexa, combining strong UX instincts, LLM quality frameworks, and partner negotiation to unblock launches and drive major engagement gains. They also bring people leadership and a thoughtful human-in-the-loop perspective on AI, especially across multilingual and culturally nuanced markets.

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SR

Mid-level Software Engineer specializing in backend systems, AI automation, and SaaS

Sunnyvale, CA5y exp
FlashyFablesUniversity of Texas at Dallas

Full-stack engineer who built and owned a production real-estate search platform (advanced search + saved-search alerts) using Next.js App Router/TypeScript with a NestJS + Postgres + Elasticsearch/Kafka backend. Demonstrated strong performance engineering (map search FPS ~20→60, ~80% latency reduction) and backend scalability (optimized alert-matching queries and orchestrated notification workflows with Airflow/Redis), with measurable post-launch engagement gains (+27% returning users).

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Aakash Khepar - Mid-level Full-Stack AI Engineer specializing in agentic AI systems in Tempe, AZ

Aakash Khepar

Screened

Mid-level Full-Stack AI Engineer specializing in agentic AI systems

Tempe, AZ4y exp
Arizona State UniversityArizona State University

Full-stack engineer with strong ownership across production SaaS and AI agent systems, including a multi-tenant enterprise analytics product at Fractal Analytics and an archive intelligence platform for a real nonprofit. Stands out for combining deep backend/system design, secure AI/RAG implementation, and rapid zero-to-one execution—plus multiple hackathon wins and leadership roles.

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SA

Mid-level Full-Stack Engineer specializing in AI-driven data platforms

Santa Barbara, CA5y exp
UberUniversity of Alabama at Birmingham

Full-stack engineer with 5+ years of experience who built real-time data visualization and analytics systems at Uber, spanning React/TypeScript frontends, Node/GraphQL services, Kafka pipelines, and PostgreSQL. Particularly compelling for teams needing a hands-on builder who can turn ambiguous customer needs into scalable products, and who has also applied RAG with LangChain/OpenAI over 1.8M support files to surface actionable insights.

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TL

Senior Full-Stack Engineer specializing in scalable web platforms

Tempe, AZ6y exp
InkSoftUniversity of Phoenix

Software engineer with 5+ years of experience building and scaling high-traffic web systems, including e-commerce-style purchasing/reservation flows and broker back-office platforms. He has hands-on experience across Next.js front ends, Python integrations, Go load-testing tools, and MySQL/Redis-backed architectures, with notable exposure to financial reporting, MT5 integrations, and commission logic.

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Melbourne Brown - Senior Software Engineer specializing in AI-driven cloud-native platforms in Atlanta, GA

Senior Software Engineer specializing in AI-driven cloud-native platforms

Atlanta, GA12y exp
McKinsey & CompanyKennesaw State University

Engineer with unusual breadth: from a tiny startup building racehorse medical-record systems on credit-card chips for live racetrack demos to modern AI-powered contract intelligence platforms in production. Brings hands-on full-stack and backend depth across React, Python, .NET, PostgreSQL, Kubernetes, and Azure, with a track record of making complex, reliability-sensitive systems work in real-world conditions.

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SH

Mid-level Software Engineer specializing in systems, storage, and machine learning

Round Rock, TX4y exp
Dell TechnologiesUniversity of Wisconsin–Madison

Robotics-focused engineer who built a non-holonomic self-driving car on Raspberry Pi 5 using ROS 2, implementing sensor fusion (robot_localization EKF), 2D SLAM (slam_toolbox), custom Hybrid A*/RRT* planners, and MPC trajectory tracking. Demonstrated strong real-time debugging and performance tuning (timestamp sync, CPU contention mitigation) and is extending the platform toward CV-based plant identification and autonomous plant watering.

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PP

Intern Software Engineer specializing in distributed systems and security

San Jose, CA6y exp
AnyLogUniversity of Pennsylvania

Built a production LLM-powered analyst assistant at Discern Security to speed up SOC investigations using a RAG pipeline over security vendor documentation (Python PDF ingestion, vector search). Demonstrates deep, security-critical LLM engineering: structure-aware chunking with custom table parsing, grounded/cited responses, prompt-injection defenses, and post-generation validation, validated via golden datasets and adversarial testing; tool is used daily by analysts.

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RV

Rucha Visal

Screened

Mid-Level Software Development Engineer specializing in distributed systems and full-stack web apps

Seattle, USA4y exp
AmazonUniversity of North Carolina at Charlotte

Software engineer who owned customer-facing, high-traffic TypeScript/React + TypeScript backend systems end-to-end, emphasizing safe velocity through feature flags, staged rollouts, observability, and rollback-ready incremental delivery. Reports shipping more frequently with fewer production incidents and faster recovery due to these guardrails.

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JS

Jonas Shuai

Screened

Mid-level Full-Stack Software Engineer specializing in cloud, microservices, and React/Java

Menlo Park, CA3y exp
Mainspring EnergyUniversity of San Francisco

Software engineer with experience at PayPal and JPMC building large-scale onboarding/account setup systems using React/TypeScript with Spring Boot/Node microservices and Kafka. Also built an Ignition-based SCADA monitoring tool at Mainspring Energy that became the default for manufacturing/test engineers by aggregating real-time telemetry and historical test data.

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SP

Sneha Patil

Screened

Mid-level Financial Analyst specializing in FP&A, forecasting, and regulatory reporting

New York, NY5y exp
JPMorgan ChaseUniversity of Texas at Arlington

Backend-focused software engineer (4+ years) across e-commerce, banking, and healthcare who owned mission-critical checkout/order management end-to-end and improved peak-traffic success rates via resiliency patterns (timeouts/retries/caching) and data-driven iteration. Also built and shipped real-time operational dashboards (React/TypeScript + Spring Boot) using WebSockets and event-stream integrations, with strong experience in Kafka/RabbitMQ-style messaging at scale.

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SS

Mid-level Business Data Analyst specializing in Financial Services and Healthcare analytics

USA4y exp
VisaGeorge Mason University

Full-stack engineer (~4 years) who has owned and shipped customer-facing SaaS onboarding and a role-based real-time analytics dashboard using TypeScript/React with a modular backend. Experienced in microservices with RabbitMQ and strong observability practices (correlation IDs, structured logging, queue metrics), and built an internal deployment tracker integrated with CI/CD that replaced manual spreadsheet/Slack processes.

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YK

Junior AI/ML Engineer specializing in applied LLMs, security, and reinforcement learning

New York, USA2y exp
New York UniversityNYU

Built and shipped a production LLM-powered investor research feature for a fintech product, focused on grounded answers and minimizing hallucinations. Implemented retrieval-quality and evidence-coverage gating with clear refusal fallbacks, and evaluates systems with regression tests and metrics like correct-refusal rate, hallucination rate, and latency. Comfortable orchestrating workflows with LangChain or custom Python depending on production needs.

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CD

Mid-Level Software Developer specializing in Java microservices and cloud-native systems

St. Louis, MO5y exp
EpsilonSaint Louis University

Backend engineer focused on cloud/distributed systems, deploying Java 17/Spring Boot microservices on AWS EKS with RDS and Kafka. Demonstrated strong production readiness work (DB lock mitigation, Kafka idempotency, gradual rollouts) and delivered a major latency improvement (~400ms to ~100ms). Also has proven cross-layer troubleshooting skills, isolating intermittent API timeouts to a specific Kubernetes node’s network interface issue, and partners closely with ops teams to build dashboards and workflow automation (including Python scripts).

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LK

Junior Full-Stack & Data Engineer specializing in cloud platforms and cybersecurity ML

New York, NY2y exp
AccentureNYU

Built a hackathon "Patient Summary Assistant" backend focused on healthcare workflows, combining RAG-based summarization with HIPAA-minded privacy controls (NER redaction + encryption). Demonstrated strong infra skills by deploying on Kubernetes with Helm/HPA and GitOps (ArgoCD), plus migrating from OpenAI to an on-prem Llama 3 stack (vLLM, quantization, shadow-mode testing) and adding real-time Kafka ingestion for patient vitals/anomaly alerts.

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NV

Junior Data & Machine Learning Engineer specializing in MLOps and NLP

Los Angeles, United States1y exp
WorkUpUSC

ML/LLM practitioner with production experience building a healthcare review sentiment pipeline (RateMDs) using Hugging Face Transformers plus a LangChain+FAISS RAG layer for interactive querying. Also led orchestration-driven optimization of Nike’s Fusion ETL pipeline, improving runtime efficiency by 20%, and has experience translating ML outputs into Tableau dashboards for non-technical healthcare stakeholders (e.g., readmission risk).

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NM

Nathan Moore

Screened

Principal Architect specializing in SRE, DevOps, and large-scale cloud/CDN platforms

Dallas, Texas14y exp
Inertia LabsUCLA

Engineering leader who drove the conception, PRD, architecture, and delivery of MaxCDN’s next-generation CDN platform ("E2"), including control plane work, hardware deployment planning, and observability/billing data processing. Also built Krypton Labs’ engineering team from the first hires, using a flat Agile structure and emphasizing constructive conflict, strong documentation, and remote-team accountability.

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SA

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

Texas, USA4y exp
PayPalNortheastern University

Worked on payments and wallet transactions, with an emphasis on observability and root-cause analysis. Delivered end-to-end A/B testing optimization and implemented Jenkins-based CI/CD automation that reduced manual implementation to 35% and cut deployments to ~2 minutes, with attention to operational considerations like on-call/call rotations.

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RC

Richard Cerow

Screened

Director of Marketing Technologies specializing in scalable web platforms for gaming

El Segundo, CA19y exp
KraftonUniversity of Notre Dame

Player-coach engineering leader focused on consumer-grade video/multimodal products and high-reliability identity/auth experiences. Led design and implementation of multi-step mobile login/MFA flows with telemetry-driven funnel improvements, shipped Node services and security fixes, and owned auth incidents end-to-end using RUM and step-level instrumentation. Introduced feature-flagged delivery and targeted review/testing practices to speed iteration ~20–30% while keeping login stability high.

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GK

Junior Full-Stack Software Engineer specializing in web platforms and data systems

Atlanta, GA2y exp
IntuitGeorgia Tech

Full-stack engineer and KICKOFFUSA cofounder who built production payment/registration and live tournament experiences under real matchday load (200+ concurrent users), including Stripe webhooks with idempotency and UX improvements that cut checkout abandonment ~15%. Also owned an end-to-end research hub at a GTSCL internship—designed a normalized Postgres schema and full-text search (tsvector/GIN) delivering sub-100ms queries for 300+ researchers.

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Pratima Singh - Senior Full-Stack Software Engineer specializing in FinTech, cloud microservices, and blockchain in Tempe, AZ

Pratima Singh

Screened

Senior Full-Stack Software Engineer specializing in FinTech, cloud microservices, and blockchain

Tempe, AZ10y exp
Arizona State UniversityArizona State University

Python/ML engineer with strong DevOps depth: built an end-to-end regime-aware stock prediction system (custom fine-tuned FinBERT sentiment + technical/macro features) delivering a 12% accuracy lift. Also implemented Kubernetes/Helm + Jenkins/GitHub Actions pipelines (including GitOps-style workflows for multi-cloud Hyperledger Besu) and improved deployment speed/stability by ~50% while addressing race conditions and image drift.

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Nagarjuna Vaddineni - Mid-level Full-Stack Software Engineer specializing in cloud-native microservices and data pipelines in Seattle, WA

Mid-level Full-Stack Software Engineer specializing in cloud-native microservices and data pipelines

Seattle, WA6y exp
AmazonTexas A&M University-Kingsville

Amazon backend engineer who built and operated high-scale Java Spring Boot microservices on AWS (EKS/EC2) handling millions of daily transactions, with deep experience debugging p95 latency and database/ORM bottlenecks. Shipped an AI-driven real-time personalization feature by integrating SageMaker model inference end-to-end with low-latency caching and graceful fallbacks, and designed robust order/payment orchestration with retries, compensations, and DLQ-based escalation.

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Sai Dinesh Pusapati - Senior AI/ML Engineer specializing in GenAI agents and LLM workflows in San Francisco, CA

Senior AI/ML Engineer specializing in GenAI agents and LLM workflows

San Francisco, CA6y exp
Scale AIBelhaven University

LLM/AI engineer with production experience building a retrieval-based document intelligence system that extracts information from PDFs/emails, backed by Python + Spark pipelines. Focused on reliability and cost/latency optimization (caching, batch processing) and has hands-on orchestration experience with Airflow (sensors, retries, alerts). Also partnered with business stakeholders to deliver customer feedback classification/summarization for faster sentiment insights.

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