Vetted Software Development Engineers in the NYC Metro

Pre-screened and vetted in the NYC Metro.

DG

Senior Software Engineer specializing in cloud-native distributed systems and mobile/web apps

New York, NY8y exp
AmazonNortheastern University
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DL

Junior Full-Stack Software Engineer specializing in Real Estate SaaS and AI automation

New York, NY2y exp
C-Star TechnologiesNYU
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RR

Mid-Level Software Engineer specializing in full-stack systems and cloud platforms

New York, NY4y exp
Goldman SachsUniversity at Buffalo
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VG

Intern Product Engineer specializing in AI-native GTM and FinTech payments

New York, NY2y exp
Victory Strategy Management IncColumbia University
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SA

Mid-Level Software Engineer specializing in cloud-native backend and LLM/RAG systems

New York, NY3y exp
LOCOMeXNYU
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Amaan Elahi - Mid-level Software Engineer specializing in backend, AI, and full-stack systems in New York, NY

Amaan Elahi

Screened

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

New York, NY5y exp
SAIL GTXNYU

Built and shipped production LLM agents including an internal RAG-based compliance classification system at SAIL (FastAPI/Redis/Docker) designed to handle real failure modes and scale to ~10k LLM calls/hour, achieving ~93% pipeline accuracy with reduced hallucination risk via multi-model orchestration and strict grounding. Also architected “Elara,” a state-machine-driven conversational appointment booking agent using structured JSON outputs and backend function execution for reliability, and has experience normalizing messy OTA/PMS data at RateGain.

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Aditya Jhaveri - Mid-level Software Engineer specializing in AI, big data, and distributed systems in Jersey City, NJ

Mid-level Software Engineer specializing in AI, big data, and distributed systems

Jersey City, NJ3y exp
New York UniversityNYU

Software Developer at NYU (GEMSS) focused on scaling and optimizing a data-heavy asset management web app, including migrating/optimizing data access via Google Sheets API and Firestore. Previously an SDE at Sainapse working on Spring Boot microservices POCs (Kafka, Hadoop at 2B+ record scale). Built an end-to-end Apple Wallet coupon generation/redemption system using PassKit + Google Apps Script with measurable ops impact (40% efficiency gain).

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Satyajit Mohanty - Mid-level Software Developer specializing in Java, Spring Boot, and microservices in Healthcare and FinTech in New York, NY

Mid-level Software Developer specializing in Java, Spring Boot, and microservices in Healthcare and FinTech

New York, NY5y exp
Elevance HealthUniversity of Florida
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Rahul Pudurkar - Mid-level Full-Stack Software Engineer specializing in AI/ML and GenAI platforms in New York, NY

Mid-level Full-Stack Software Engineer specializing in AI/ML and GenAI platforms

New York, NY5y exp
JPMorgan ChaseSyracuse University
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AV

Senior AI/ML Systems Architect specializing in cloud-native MLOps and GenAI

Jersey City, NJ7y exp
JPMorgan ChaseUniversity of Pittsburgh
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AS

Junior Software Engineer specializing in AI systems, logistics, and FinTech

New York, NY2y exp
StarboardNYU
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SA

Mid-Level Full-Stack Software Engineer specializing in cloud and scalable web systems

New York, NY3y exp
Find CommerceUniversity of Cincinnati
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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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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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AP

Ankit Patra

Screened

Mid-Level Software Engineer specializing in cloud, microservices, and AI/ML

New York, NY6y exp
Binghamton UniversityBinghamton University

Backend/API engineer with ~4 years experience building production services in .NET Core/PostgreSQL/Redis/Docker and optimizing real-world latency issues (claims ~60% response-time improvement). Also built and owned an end-to-end RAG-based AI assistant using Python/FastAPI, OpenAI APIs, and Pinecone, plus agentic workflows with reliability guardrails (retries, confidence thresholds, monitoring). Currently pursuing a master’s degree and targeting a $150k base salary.

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NZ

Mid-level Full-Stack Software Engineer specializing in FinTech and web applications

Raritan, NJ6y exp
NelnetDelaware County Community College
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AM

Senior Full-Stack/Platform Engineer specializing in cloud, Kubernetes, and AI automation

New York City, NY3y exp
Global Key SolutionsNYU
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Vedang Jadhav - Mid-Level Software Engineer specializing in cloud-native microservices on AWS in New York City, NY

Vedang Jadhav

Screened

Mid-Level Software Engineer specializing in cloud-native microservices on AWS

New York City, NY5y exp
CitigroupIndiana University Bloomington

Backend engineer with experience across healthcare and fintech platforms (Anthem, Citia) building high-throughput Python microservices with strong compliance/security focus (HIPAA, tenant isolation). Has integrated ML workflows into production systems (ResNet embedding-based image similarity) using async pipelines (Celery/Redis) and AWS (Lambda/S3/ECS), delivering measurable performance and fraud/content-integrity improvements at scale.

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Tara Worrell - Senior Software Engineer specializing in backend systems, AI/LLM integration, and cloud infrastructure in Brooklyn, NY

Tara Worrell

Screened

Senior Software Engineer specializing in backend systems, AI/LLM integration, and cloud infrastructure

Brooklyn, NY6y exp
AuraCodeBinghamton University

Backend engineer with experience in highly regulated and high-stakes systems, including an airline crew messaging platform requiring near-zero-error real-time operations and a HIPAA-compliant mental health application built from an early-stage concept. They also show strong operational maturity, having owned a GoDaddy production incident through resolution and then led deployment pipeline improvements that reduced build failures by 40% and doubled deployment frequency.

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NM

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

New Brunswick, NJ4y exp
PTCUniversity of Maryland, Baltimore County

JavaScript/Node.js engineer who contributes to open-source utilities focused on API integrations and JSON validation, including a 30–35% throughput improvement by profiling and optimizing deep-clone-heavy code paths. Strong in performance tooling (Node performance hooks, Chrome DevTools flame graphs), incremental/test-driven changes, and community-facing issue triage plus developer-friendly documentation.

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Mehul Sudrik - Mid-level Full-Stack Software Engineer specializing in web, mobile, and cloud-native systems in Jersey City, NJ

Mid-level Full-Stack Software Engineer specializing in web, mobile, and cloud-native systems

Jersey City, NJ4y exp
Jo Strong LLCNYU
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SJ

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

Harrison, NJ5y exp
MetLifeStevens Institute of Technology
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Sumanth Gottipati - Mid-level Full-Stack Software Engineer specializing in cloud-native microservices and FinTech in New York, NY

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

New York, NY4y exp
Delta Air LinesVirginia University of Science and Technology

At Delta Airlines, built and shipped a production LLM-powered semantic search/troubleshooting assistant over maintenance logs and operational documentation using OpenAI embeddings and a vector database. Implemented hybrid ranking, query enrichment, and structured filters to improve relevance ~35% while optimizing latency via caching and vector tuning. Also designed a scalable Kafka + AWS (Lambda/SQS) ingestion pipeline with strong reliability/observability and an eval loop using real engineer queries and human review.

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