Vetted Engineering Professionals in the NYC Metro

Pre-screened and vetted in the NYC Metro.

DC

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

New York, NY6y exp
KPMG
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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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Fatema Tuzzohra - Senior Full-Stack Java Developer specializing in banking and healthcare platforms in Hicksville, NY

Senior Full-Stack Java Developer specializing in banking and healthcare platforms

Hicksville, NY12y exp
U.S. BankKhulna Women's College

Enterprise-focused full-stack/backend engineer with hands-on experience shipping a production LLM-powered document analysis platform for internal operations teams. They combine cloud-native microservices expertise across AWS/Azure with practical agent-system design, including async orchestration, model routing, observability, and safeguards for hallucinations, failures, and human-review fallbacks.

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SG

Senior Full-Stack Software Engineer specializing in cloud microservices and data platforms

New York, NY9y exp
S&P GlobalUniversity of Texas at Dallas
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NK

Naga Karumuri

Screened ReferencesStrong rec.

Mid-Level Full-Stack Engineer specializing in AI and 3D computer vision

Newark, NJ4y exp
DiffStudioNJIT

Built and productionized an LLM-driven document verification workflow for a construction firm’s submittals process, moving from a Vercel/Next.js prototype to a FastAPI + LangChain/LangGraph backend with background workers and multi-server deployment. Uses LLM tools (e.g., OpenAI Codex/Cloud Code) for rapid development and log-driven root cause analysis, and partners with customer teams on evaluation metrics and iterative improvements.

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JL

Joseph Lin

Screened ReferencesModerate rec.

Intern Software Engineer specializing in full-stack development and applied AI

New York, NY0y exp
Real Value CapitalNYU

Internship experience building an end-to-end medical AI pipeline that extracts and normalizes messy medical PDFs, fine-tunes BioBERT to classify tumor-related statements (including negation/ambiguity handling), and integrates image-model outputs (MedSAM/GroundingDINO) for tumor localization and classification. Also worked on an LLM/RAG system to draft IPO prospectuses using retrieved regulatory/financial sources (including SEC EDGAR) with structured prompts to reduce hallucinations.

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JL

Julian Lee

Screened

Intern Software Engineer specializing in AI/LLMs and full-stack development

New York, New York1y exp
Highlight.AIUSC

AI/ML infrastructure-focused engineer who has built production RAG systems from scratch (Supabase/pgvector + OpenAI embeddings) and iterated using formal eval metrics to improve retrieval quality. Also debugged real-time audio issues in a LiveKit-based pipeline by correlating packet loss with VAD behavior, and has deep experience building brittle, customer-specific financial platform integrations in Python/Playwright (2FA, redirects, token refresh, rate limits).

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VS

Senior Full-Stack Java Developer specializing in cloud-native microservices and real-time web apps

New York, USA5y exp
SeatGeekPace University

Full-stack engineer/product owner who built and scaled a customer-facing job application portal (Skillbridge) using TypeScript/React and Spring Boot/MongoDB, optimizing search performance with indexing, caching (Redis), and payload/lazy-loading improvements. Also built an internal AI-driven analytics dashboard for Salesforce operations using OpenAI sentiment analysis, achieving 70% reduction in manual analysis and driving adoption through demos and iterative feedback.

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AD

Aelina Das

Screened

Senior Software Engineer specializing in risk systems and event-driven data pipelines

Whippany, NJ8y exp
BarclaysNortheastern University

Backend engineer with recent Barclays experience building a Python asyncio + Kafka risk reporting service for trading desks, including a major refactor from blocking batch processing to event-driven incremental pipelines to restore intraday/EOD performance. Also shipped an applied AI feature using OpenAI fine-tuning to classify risk-breach severity and generate trader/risk-manager summaries with robust retry/fallback handling, plus demonstrated strong database/query optimization (triggers, materialized views, partial indexes) in a risk-limits/breaches domain.

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SS

Shivam Sah

Screened

Mid-level Backend Software Engineer specializing in distributed microservices

New York, United States4y exp
ActiveViamNortheastern University

Internship at ActiveVM where they tackled large-scale Spring Boot 2→3/library migrations across hundreds of downstream products by combining OpenRewrite (AST-based recipes) with an LLM/RAG-based classifier that routed risky files to human experts. Reported ~70% reduction in manual effort and 90%+ accuracy after testing across multiple branches and cutovers; also built a CTR-driven book recommendation capstone showcased at the Google office in Cambridge.

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Dylan Zhu - Mid-level Machine Learning Engineer specializing in computer vision and generative AI in Hoboken, NJ

Dylan Zhu

Screened

Mid-level Machine Learning Engineer specializing in computer vision and generative AI

Hoboken, NJ7y exp
Stevens Institute of TechnologyPurdue University

Built and deployed an LLM/RAG system that uses differential privacy and distributional similarity checks to transform private data into a non-sensitive knowledge base while preserving utility. Also has experience demonstrating adversarial ML concepts (FGSM) to non-technical audiences by focusing on observable model behavior rather than implementation details.

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Priyanshi Sharma - Mid-level Software Engineer specializing in FinTech full-stack and backend systems in Parsippany, NJ

Mid-level Software Engineer specializing in FinTech full-stack and backend systems

Parsippany, NJ4y exp
ADPVirginia Tech

Built and productionized a GenAI prompt-engineering solution to retrieve prevailing wages based on job/location selections, emphasizing accuracy through stricter prompt templates and validation. Hands-on in real-time production debugging using Splunk (callback tracing, verbose logging, header inspection) and experienced running developer-facing demos/workshops that helped drive marketplace API adoption.

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AG

Aninda Ghosh

Screened

Mid-level Software Engineer specializing in FinTech and full-stack platforms

New York, USA5y exp
Parallel WorldsNYU

Enterprise-minded builder who has owned complex, high-impact systems from discovery through stabilization, including a customer master data platform at AB InBev serving 2,000 sales reps across 13 countries. Also demonstrates strong AI product instincts, having built a first-place ReAct-style NYC property intelligence agent at IBM's AI Demystified Hackathon, while showing deep rigor in data quality, integrations, and production reliability.

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RM

Rahul Manne

Screened

Mid-level Software Engineer specializing in .NET, Azure, and enterprise platforms

New Brunswick, NJ4y exp
Johnson & JohnsonClark University

JavaScript/React/TypeScript engineer with hands-on open-source experience improving a hooks utility library—fixed a reported async race condition that reduced unexpected re-renders and added a debounced callback hook that became widely used. Brings a production-minded approach to performance and abstractions (APM/metrics-driven, DB/caching focus) with strong testing, documentation, and community support practices.

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Sanjana Chowdary - Intern Full-Stack Engineer specializing in web applications and AI in New York, NY

Intern Full-Stack Engineer specializing in web applications and AI

New York, NY2y exp
GrouprNYU

Engineer with hands-on experience both using AI coding agents in production and building AI systems, including chatbot development and BERT fine-tuning at Atos. At Groupr, they applied strong systems judgment to live operational workflows, validating concurrency decisions manually for an admin portal supporting 500+ orders per day.

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Brian Lam - Mid-level Full-Stack Engineer specializing in AI and FinTech in New York, NY

Brian Lam

Screened

Mid-level Full-Stack Engineer specializing in AI and FinTech

New York, NY12y exp
Couplr AIApp Academy

Frontend-focused engineer working in Next.js/React who has owned complex internal and partner-facing browser workflows, including a multi-step CSV onboarding wizard and an admin quiz editor. Stands out for practical debugging skill on production-only timezone issues and for building resilient, typed form-heavy UIs with strong error handling.

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SK

Mid-Level Software Engineer specializing in FinTech microservices and AI automation

New York City, United States3y exp
Bank of AmericaNJIT

Backend engineer with experience evolving a real-time transaction and rewards processing platform from a tightly coupled architecture into domain-based microservices. Uses REST plus Kafka for synchronous vs. asynchronous workflows, and builds Python/FastAPI APIs with Pydantic contracts, Docker/Kubernetes deployments, and JWT/OAuth-based security; has also supported analytics/dashboard use cases (Power BI).

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GN

Gordon Ng

Screened

Mid-Level Software Engineer specializing in AI/ML and distributed systems

Brooklyn, NY3y exp
OptumBoston University

Software engineer with production experience building a serverless monolith and multi-layer video pipeline at easyML, plus hands-on integration of multiple LLM providers (Grok/Claude/OpenAI) into a full-stack app. Interested in robotics via computer vision (OpenCV/OpenMMLab), with a strong real-time systems mindset around SLOs, latency, determinism, and reliability; also has low-level OS experience writing a keyboard device driver.

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Prachika Agarwal - Senior Solutions Architect and Data Analyst specializing in cloud data platforms and experimentation in New York, NY

Senior Solutions Architect and Data Analyst specializing in cloud data platforms and experimentation

New York, NY4y exp
Ovative GroupNYU

Software engineer who built and scaled an internal automation/auditing tool for analyzing Google and Adobe tagging containers, adopted by 13 internal clients and saving ~15 hours per audit. Has experience shipping containerized, Kubernetes-orchestrated systems and integrating OpenAI APIs into an agentic chatbot feature (plus prior NLP chatbot work during a Cyber Peace Foundation internship).

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YL

Yaoxin Liu

Screened

Intern Software Engineer specializing in backend and full-stack systems

New York, NY1y exp
SevenRoomsNYU

Built and iterated an end-to-end virtual waiting room for a real-time ticketing prototype, making concrete architecture tradeoffs (polling + Redis Pub/Sub) and improving performance post-launch with Redis caching (+30% throughput, -15% p99 latency). Also has hands-on experience building Spark/HDFS ETL pipelines with strong reliability/observability patterns and running disciplined NLP model evaluation loops on review-rating classification.

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RJ

Rohit Jaiswal

Screened

Mid-level Software Engineer specializing in distributed backend systems for FinTech

New York, NY5y exp
JPMorgan ChaseSyracuse University

Full-stack/backend-leaning engineer with experience spanning fintech platforms, internal AI/RAG assistants, real-time analytics systems, and a zero-to-one academic web platform. Stands out for combining hands-on backend and infrastructure work with product ownership, team guidance, and measurable impact like cutting troubleshooting lookup time from 30 minutes to under 8 minutes and creating reusable UI components adopted across multiple projects.

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NT

Mid-level Software Engineer specializing in full-stack cloud-native systems

New York, NY7y exp
Dune SecurityNYU

Backend/platform engineer from Dune Security with strong experience turning messy, fragmented workflows into reusable production systems. They’ve built a shared database abstraction layer, integrated multiple enterprise security platforms into a unified workflow, and shipped AWS Bedrock-powered security insight features with guardrails and human review.

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RM

Rifat Mahfuz

Screened

Junior Backend Software Engineer specializing in microservices and API platforms

New York City, NY1y exp
ShareTripUniversity of Illinois Urbana-Champaign

Backend engineer with strong performance and security instincts: built a Flask API for readability metrics with clean, testable modular design; optimized SQLAlchemy/Postgres to eliminate N+1 issues (800ms to 120ms). Also implemented an LLM-powered natural-language travel search using Claude Sonnet + Amadeus with RAG and anti-exploitation safeguards, plus multi-tenant isolation via Postgres RLS and Redis caching that cut search latency from ~20s to ~4–5s while reducing storage costs.

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