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Vetted LangGraph Professionals

Pre-screened and vetted.

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Ambikadevi Damodaran

Screened

Principal Engineer specializing in GenAI/LLM platforms and enterprise modernization

Hayward, California19y exp
Realtor.comTexas State University

“Built a production LLM-driven personalization microservice for realtor.com using LangChain/LangSmith with an MCP tool layer and RAG to generate schema-constrained ranked listings in real time, replacing a rule-based engine and improving engagement/lead conversion. Also owned an ambiguous cross-channel identity initiative, implementing an identity graph via Twilio Unify with required SDK and data-warehouse integration.”

Adobe PhotoshopAgileAJAXAPI DesignAPI GatewayAuthentication+149
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RS

Ravi Subramanian

Screened

Executive Technology Leader specializing in B2C marketplaces, cloud platforms, and AI products

San Francisco, CA17y exp
KeyCentrixMadurai Kamaraj University

“20-year technology builder with ~8 years in healthcare AI, currently at Keycentrix modernizing a legacy pharmacy solutions business. Shipped an OCR MVP within days and delivered a rebate-based product generating ~$50K/month, leveraging Claude/LangGraph agentic automation to replace work typically requiring a much larger engineering team. Developing a "Longevity AI Copilot" B2B platform that synthesizes research, labs, and wearable data into personalized longevity protocols for HNW and corporate wellness markets; concept validated but not yet incorporated or funded.”

A/B TestingAPI DevelopmentAutomated TestingAutomationAWSAWS Lambda+125
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SS

Sai Srinivasa Subrahmanyam Puranam

Mid-level AI/ML Engineer specializing in NLP, Generative AI, and fraud detection

Centennial, CO4y exp
Capital OneUniversity of Colorado Boulder
A/B TestingAnomaly DetectionAWSAWS LambdaBERTCaching+92
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TM

Tejal Meda

Mid-level Backend/Platform Engineer specializing in distributed systems and data platforms

Bangalore, India3y exp
Schneider ElectricUniversity of Texas at Austin
PythonRC++SQLREST APIsDjango+74
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AM

Andrew Mendola

Senior Full-Stack Engineer specializing in Python, cloud-native systems, and LLM applications

Remote14y exp
IntelUniversity of Miami
PythonJavaScriptTypeScriptSQLJavaGo+142
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AS

Abhijeet Satish Ringe Abhijeet Satish Ringe

Junior ML Engineer specializing in GenAI agents, RAG, and computer vision

San Jose, CA2y exp
AdobeSyracuse University
C#CC++JavaPythonGo+73
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JL

Jiahao Liu

Mid-level AI/Software Engineer specializing in LLM agents and RAG systems

Somerville, MA3y exp
MobiBrown University
PythonJavaSQLAWS GlueAWS LambdaDocker+71
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TS

Tamanna Sharma

Mid-level GenAI & Analytics Engineer specializing in LLM and cloud cost/finance analytics

San Francisco, CA6y exp
Owens CorningUC Davis
Generative AIMachine LearningLarge Language Models (LLMs)Retrieval-Augmented Generation (RAG)LoRAForecasting+62
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SC

Sai charan Kodadi

Mid-level Machine Learning & Generative AI Engineer specializing in enterprise RAG and MLOps

Remote5y exp
GEICOGuru Nanak Institutions Technical Campus
PythonRSQLPySparkScikit-learnTensorFlow+118
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SS

Shawn Souto

Director of Engineering specializing in GenAI and scalable enterprise platforms

Newport Beach, CA18y exp
SAPDeVry University
AgileArgo CDAWSCI/CDC#Datadog+85
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SK

Shubham Kumar

Junior AI Research Engineer specializing in NLP, speech and generative AI

Gurugram, India3y exp
SHLG.L. Bajaj Institute of Technology and Management
Anomaly DetectionAWSC++Computer VisionDeep LearningDjango+40
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SJ

saniya jaswani

Senior Data Scientist specializing in Generative AI and NLP

9y exp
AcquiaIIT Jodhpur
A/B TestingAmazon CloudWatchAmazon EC2Amazon S3Amazon SageMakerAWS+71
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VD

Vishakha Dikshit

Mid-level Machine Learning Engineer specializing in LLMs, RAG, and document intelligence

Bloomington, IN5y exp
Project 990Indiana University
PythonCC++JavaTypeScriptJavaScript+72
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MS

Miguel Saldana

Senior AI/ML Engineer specializing in GenAI, MLOps, and healthcare analytics

Chicago, IL13y exp
WezomRice University
A/B TestingAgileAmazon ECSAmazon EKSAmazon RedshiftAnomaly Detection+359
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PC

Prathamesh Channe

Intern AI/Backend Engineer specializing in LLM agents and cloud microservices

San Jose, CA2y exp
NutanixUC Irvine
PythonJavaCSQLJavaScriptSpring Boot+55
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YB

Yusuf Baig

Mid-level Machine Learning Engineer specializing in LLMs, multimodal AI, and backend systems

New York City, NY4y exp
Canyon CodeNYU
PythonC++CC#SQLJavaScript+57
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SB

Shiyan Boxer

Mid-Level Software Engineer specializing in GenAI and FinTech

San Francisco, CA6y exp
CascaQueen's University
PythonTypeScriptJavaScriptRubyReactReact Native+52
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SL

silin liu

Screened

Mid-level AI/ML Engineer specializing in LLM agents, RAG, and enterprise ML systems

New York City, NY5y exp
Metropolitan Transportation AuthorityStevens Institute of Technology

“Built a production multi-agent recommendation/RAG system for internal data analysts to speed up weekly report creation by improving document discovery and automating report/SQL generation. Implemented LangGraph-based orchestration with deterministic agent routing, robust error handling (interrupt/resume), and metadata-driven semantic chunking for diverse PDF/document formats, plus monitoring for latency, throughput, and token/cost efficiency.”

LangGraphLangChainPrompt EngineeringHugging Face TransformersOpenAI APISemantic Search+118
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KM

keerthana medaveni

Screened

Mid-Level AI/ML Software Engineer specializing in agentic LLM systems

Dallas, Texas6y exp
DatatronUniversity of West Florida

“Built and deployed a production LLM-powered multi-agent compliance copilot (life sciences/finance) using LangChain/LangGraph + RAG over vector databases, delivered via async FastAPI on Kubernetes. Emphasizes audit-ready, deterministic outputs with schema constraints and citations, plus rigorous evaluation/monitoring; reports 60%+ reduction in manual research time and successful production adoption.”

AgileAJAXAmazon DynamoDBAmazon S3AngularApache Hadoop+142
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JT

Jingyi Tian

Screened

Junior Machine Learning Engineer specializing in MLOps and LLM/RAG systems

Houston, TX2y exp
Daxwell, LLCColumbia University

“LLM/agentic workflow builder focused on productionizing document-processing systems. Redesigned pipelines with LangGraph + RAG, schema-aware validation, and eval/monitoring loops; known for fast incident diagnosis (restored accuracy from ~70% to >95% same day). Partners closely with sales and stakeholders to deliver tailored demos and drive adoption (reported +40%).”

PythonRSQLTableauXGBoostMachine Learning+65
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SS

Shreyansh Srivastava

Screened

Mid-Level Full-Stack Software Engineer specializing in API-first microservices and cloud platforms

Arlington, TX4y exp
University of Texas at ArlingtonUniversity of Texas at Arlington

“Backend-focused engineer who built a resume processing and job application platform using Python/MongoDB/Streamlit, including OpenAI-powered skill/keyword extraction and recruiter-facing search/filtering. Has hands-on cloud deployment experience on AWS/Azure and executed an on-prem reservation portal migration to Azure using a phased trial-and-cutover approach; also automated CI/CD with Jenkins and GitHub Actions.”

AuthenticationAuthorizationAWSAWS LambdaAzure DevOpsBootstrap+91
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SM

Shravya M

Screened

Senior AI/ML Engineer specializing in NLP, LLMs, and MLOps

Texas, USA6y exp
CVS HealthUniversity of North Texas

“LLM/agent workflow engineer with healthcare experience (CVS/CBS Health) who built and deployed a production call-insights platform using Azure OpenAI + LangChain/LangGraph, including sentiment and compliance checks. Demonstrates deep HIPAA/PHI handling (tenant-contained processing, redaction, RBAC/encryption/audit logging) and production rigor (testing, eval sets, validation/retries, autoscaling) to scale to thousands of transcripts.”

A/B TestingAgileAnomaly DetectionApache AirflowAzure Data FactoryAzure Machine Learning+139
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NN

Neha Nadiminti

Screened

Mid-level AI/ML Engineer specializing in Generative AI and MLOps

4y exp
WalgreensUniversity of North Texas

“Built and deployed a production Retrieval-Augmented Generation (RAG) platform in a healthcare setting to automate clinical documentation review and summarization, targeting near-real-time, explainable outputs. Emphasizes grounded generation to reduce hallucinations, latency optimizations (chunking/embedding reuse), and PHI-safe workflows with access controls, plus strong orchestration experience using Apache Airflow.”

A/B TestingAnomaly DetectionApache AirflowAudit LoggingAWSAWS Glue+153
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