Vetted TypeScript Professionals

Pre-screened and vetted.

FK

Senior Java Full-Stack Developer specializing in cloud-native microservices and FinTech

Bristow, VA9y exp
Bank of America
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PA

Mid-level Full-Stack Developer specializing in React and Python (Django/FastAPI)

Toronto, Canada6y exp
The Home Depot
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VN

Mid-Level Java Software Developer specializing in cloud microservices and APIs

3y exp
Humana
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KT

Mid-level Java Full-Stack Developer specializing in microservices and cloud platforms

Florida, USA4y exp
JPMorgan Chase
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KK

Senior Full-Stack Engineer specializing in cloud-native Java microservices and GenAI

New York, NY7y exp
JPMorgan Chase
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SP

Mid-level Full-Stack Engineer specializing in AI-powered enterprise applications

US6y exp
BioNTech
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SK

Senior Full-Stack Java Developer specializing in microservices and Healthcare/FinTech systems

Seattle, WA5y exp
T-Mobile
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NC

Senior QA/Test Lead specializing in enterprise commerce platforms and order-to-cash automation

Durham, USA18y exp
Cisco
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DC

Mid-level Full-Stack Engineer specializing in Java (Jakarta EE) and React/Angular

New York, NY6y exp
KPMG
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PS

Senior Frontend Engineer specializing in React applications

San Jose, CA10y exp
Cisco
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TS

Senior Full-Stack Developer specializing in cloud-native microservices (AWS)

Irving, TX8y exp
U.S. Bank
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AS

Executive engineering leader specializing in AI, FinTech, and cloud platforms

San Carlos, CA25y exp
Presto Phoenix, Inc
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DW

Senior Front-End Engineer specializing in React platforms and web experiences

New York City, NY8y exp
Rockstar Games
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SB

Mid-level Full-Stack Software Engineer specializing in enterprise healthcare and telecom

Dallas, TX5y exp
Cigna
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AJ

Anshul Joshi

Screened ReferencesStrong rec.

Mid-Level Software Engineer specializing in distributed systems and GenAI

Austin, TX4y exp
University of Texas at AustinUniversity of Texas at Austin

Capgemini engineer with 4+ years building and deploying high-availability, low-latency fraud detection APIs and multi-cluster distributed systems for a Fortune 20 bank, including zero-downtime production rollouts and multi-layer (SQL/network/hardware) performance debugging. Also built a Python + OpenAI/LangChain LLM-powered grading workflow for Austin School for Women, cutting feedback time from 90 minutes to 5 minutes per submission for 200+ learners.

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Satya Kumar Itekela - Senior Frontend Engineer specializing in high-performance React/Next.js web apps in Remote, Canada

Satya Kumar Itekela

Screened ReferencesStrong rec.

Senior Frontend Engineer specializing in high-performance React/Next.js web apps

Remote, Canada8y exp
AutodeskDalhousie University

Frontend engineer with experience at Autodesk and Quantify, leading and scaling Next.js/React + TypeScript products from architecture through QA. Strong focus on performance (Core Web Vitals, ISR, caching/CDN) and real-time interfaces (WebSockets, Chart.js/D3), with measurable wins like 30–40% bundle reduction and ~60% less data overfetching using GraphQL/Apollo.

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KM

Kimberly Michela

Screened ReferencesStrong rec.

Junior Full-Stack Software Engineer specializing in web apps and developer tools

Toronto, Canada1y exp
Game of StreaksUniversity of Toronto

Frontend engineer who built the full frontend for gameofstreaks.com using React/Next.js with an emphasis on responsive design, accessibility, SEO, and performance profiling. Has experience refactoring legacy HTML/CSS/JS sites into reusable React components and shipping quickly with unit tests, CI/CD, and branch-based deployments; also collaborates with designers in hackathon settings (e.g., an AI interview practice app).

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Deeksha V - Mid-Level Software Engineer specializing in cloud data platforms and FinTech payments in Atlanta, GA

Deeksha V

Screened ReferencesStrong rec.

Mid-Level Software Engineer specializing in cloud data platforms and FinTech payments

Atlanta, GA4y exp
Delta Air LinesUniversity of Central Florida

Backend engineer focused on financial systems, having evolved payments and reconciliation platforms using Python/FastAPI and PostgreSQL with an emphasis on idempotency, validation, and consistency. Has led monolith-to-services migrations using feature flags and shadow traffic, and implements defense-in-depth security (OAuth2/JWT plus DB-level row security) for multi-tenant environments.

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CF

Cheryl Fernandes

Screened ReferencesStrong rec.

Senior Full-Stack AI Engineer specializing in enterprise workflow and LLM systems

Remote12y exp
OrcasoundUniversity of Illinois Chicago

Cheryl Fernandez is a frontend/platform engineering leader who has built complex real-time products in highly regulated healthcare and enterprise investigation environments. She combines deep React/TypeScript and streaming architecture expertise with cross-functional ownership across APIs, infrastructure, device behavior, and product strategy, including modernizing FDA-audited remote patient monitoring systems and adding AI-assisted workflows at EY.

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KP

KrishnaVarshith Pabbisetty

Screened ReferencesStrong rec.

Mid-level Backend Software Engineer specializing in Spring Boot, microservices, and cloud-native AI

Bay Area, CA4y exp
TemenosSan José State University

Backend engineer with experience modernizing a large-scale procurement platform at Jio Platforms by breaking a monolith serving 35 business units into Spring Boot microservices, improving uptime and cutting report latency ~30%. Also built high-concurrency FastAPI systems (200ms at ~500 concurrent users) with strong security (JWT/OAuth2/RBAC), event-driven Kafka integrations, and reliability patterns like exactly-once delivery for ~1M monthly triggers.

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RO

Rafael Ortega

Screened ReferencesStrong rec.

Senior Full-Stack & AI Engineer specializing in LLM integrations and cloud-native systems

Remote (Texas)8y exp
BlocUnitedNew Mexico Tech

Backend/data engineer with hands-on production experience building FastAPI Python APIs and AWS-native platforms (Lambda/API Gateway, SQS, ECS Fargate) with Terraform + GitHub Actions CI/CD and strong reliability practices (JWT/RBAC, retries/timeouts, structured errors/logging). Also built AWS Glue ETL pipelines (S3/RDS to curated S3/Athena) with schema evolution and data quality controls, modernized legacy processing via parallel-run validation and phased cutovers, and has demonstrated SQL tuning impact (seconds to <200ms) plus incident ownership for batch pipeline SLAs.

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