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Vetted LangChain Professionals

Pre-screened and vetted.

LangChainPythonDockerSQLAWSCI/CD
PK

Pranjal Kamboj

Junior Machine Learning Engineer specializing in Generative AI and LLM agents

San Jose, CA1y exp
GuardiumAIUniversity of Texas at Arlington
PythonJavaTypeScriptSQLApache SparkPandas+67
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NB

Nitish Bayarapuneni

Junior Data Scientist specializing in machine learning and analytics

Remote1y exp
BlackBuck EngineersUniversity of Central Missouri
PythonRSQLScalaMachine LearningDeep Learning+55
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PV

Patoliya Viral

Mid-level Generative AI Engineer specializing in LLMs, RAG, and agentic systems

Surat, India4y exp
Arize AIGreat Learning
ClaudeData cleaningData pipelinesGPTHugging FaceLangChain+66
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AK

Anand Kamble

Junior AI Engineer specializing in LLM systems and RAG

San Francisco, CA2y exp
Liebre.aiFlorida State University
AWSBashCC++CypressDocker+63
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RG

Rutvik Gadhiya

Mid-level AI/ML Engineer specializing in NLP, LLMs, RAG, and MLOps

Austin, TX5y exp
Royal Monarch Solutions LLCUniversity of the Pacific
A/B TestingApache HiveApache KafkaApache SparkAWSAWS Glue+97
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RE

Russell Elliott

Junior Full-Stack Developer specializing in AI integrations and LLM research

Santa Cruz, CA3y exp
University of California, Santa CruzUC Santa Cruz
Amazon EC2Amazon S3AngularJSAPI IntegrationAWSC+64
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RP

Rohith Perumandla

Mid-level AI/ML Research Engineer specializing in NLP, LLM agents, and multimodal systems

Chicago, IL4y exp
DePaul UniversityDePaul University
Cloud ComputingData AnalysisData StructuresDeep LearningDjangoFeature Engineering+69
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LC

Lokesh Chaganti

Mid-level AI/ML Engineer specializing in GenAI, agentic AI, and RAG pipelines

USA4y exp
DoubleneIndiana Wesleyan University
AWSAWS LambdaBERTCI/CDContainerizationData Preprocessing+59
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DS

Dorisa Shehi

Mid-Level Full-Stack Software Engineer specializing in web apps and AI-powered tools

Madison, WI4y exp
BoberdooHunter College
AgileAWSAWS LambdaBootstrapDockerEmbeddings+49
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AD

Amey Dabhade

Junior AI Engineer specializing in production RAG systems and GPU-accelerated inference

Pune, India1y exp
GDOMaharashtra State Skills University
API IntegrationAWSCI/CDChromaDBClaudeContainerization+92
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TW

Thomas Whidden

Senior Full-Stack Developer specializing in AI-driven SaaS and real-time analytics

Washington, DC7y exp
servertrack.ai
Next.jsTypeScriptReactPythonGoNode.js+74
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HI

Haeshitha Indukuri

Screened ReferencesStrong rec.

Entry AI/ML Engineer specializing in Generative AI, LLMs, and MLOps

Denton, TX1y exp
University of North TexasUniversity of North Texas

“Built and productionized a MediCloud/Medicoud LLM microservice platform that lets clinicians query medical data in natural language, orchestrating multi-step RAG-style workflows with LangChain and evaluating/debugging with LangSmith. Delivered measurable gains (consistency ~70%→90% / +20%; latency ~2.0s→1.1s / -40%) by implementing structured prompts, fallback logic across multiple LLMs, hybrid retrieval tuning, and AWS Lambda performance optimizations (package size, async, caching).”

Generative AILarge Language Models (LLMs)Retrieval-Augmented Generation (RAG)Prompt EngineeringGPT-4BERT+89
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JK

Jeevan Kumar

Screened

Mid-level Full-Stack AI Engineer specializing in LLM systems and RAG

Remote, USA5y exp
Augmented AIUniversity of Massachusetts Dartmouth

“Built and shipped a production "Campaign AI" multi-agent system (LangGraph) that personalizes B2B outbound emails at scale using Apollo.io prospect data, clustering-based segmentation, and 21 persona variants. Notably uncovered that high click rates were largely email security scanners and created a validated bot-detection/scoring pipeline (timestamps/IP/user-agent/click patterns), bringing reported engagement down from ~40% to a trusted 5–8% that aligned with real conversions.”

AgileAWSAWS LambdaAzure Blob StorageCI/CDDocker+150
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HV

Harshit Vashisth

Screened

Junior AI Engineer specializing in LLMs, RAG systems, and MLOps

Remote, United States1y exp
Concept2ActionJaypee Institute of Information Technology

“Robotics software engineer who built an end-to-end system ("justmatrix"), focusing on multi-agent orchestration and a multi-RAG retrieval backend/API. Has hands-on ROS experience, including a custom node for reliable high-frequency sensor data routing, plus deployment automation using Docker, Kubernetes, and CI/CD.”

Azure Machine LearningC++CI/CDCloud ComputingCSSData Structures and Algorithms+99
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MJ

Mahaboob Johny

Screened

Mid-level Data Analyst specializing in SQL/Python analytics, ETL pipelines, and BI dashboards

Denton, TX4y exp
Alenotech SolutionsFlorida Atlantic University

“Data/AI practitioner who built a production LLM-driven healthcare claims analytics and dashboarding system to reduce avoidable ER visits—processing 1.4M+ claims, flagging 19% as non-emergent, and projecting ~$2.8M in annual savings. Demonstrates strong real-world LLM reliability and performance engineering (grounding, numeric validation, caching, materialized views, quantization) plus orchestration experience with Airflow and Azure Data Factory.”

SDLCAgileWaterfallPythonRSQL+85
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AP

Aniket Patel

Junior AI/ML Researcher specializing in deep learning, computer vision, and LLM applications

Ashland, OH2y exp
Ashland UniversityAshland University
AWSBashBERTCI/CDComputer VisionC+++81
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AK

Abhishek Kandi

Mid-level Generative AI & ML Engineer specializing in LLMs, RAG, and MLOps

Frisco, TX4y exp
DoubleneBelhaven University
AgileAnomaly DetectionAPI DevelopmentCI/CDData PipelinesData Visualization+78
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SH

Sri Harsha Godavarthi

Senior Full-Stack AWS Developer specializing in cloud-native microservices and serverless systems

Irving, TX4y exp
Chicago Education Advocacy CooperativeSathyabama Institute of Science and Technology
PythonJavaTypeScriptSQLShell ScriptingNext.js+129
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SC

sravya chandolu

Junior Software/AI Engineer specializing in LLM agents and RAG systems

California, USA2y exp
California State University, FullertonCalifornia State University, Fullerton
A/B TestingAgileAmazon BedrockApache SparkAWSBERT+85
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MR

Md Rifat Ullah

Screened

Mid-level AI/ML Engineer specializing in NLP, GenAI, and conversational AI

Indianapolis, IN4y exp
Indiana University IndianapolisIndiana University Indianapolis

“Built and deployed a production bilingual (Bengali/English) AI virtual assistant that replaced IVR for telecom customer service at massive scale (~15M users), integrating ASR/TTS, Rasa dialogue management, and custom NLP. Overcame low-resource Bengali data and noisy call-center audio with synthetic data augmentation and transformer fine-tuning, achieving significant production gains including ~50% reduction in support calls.”

PythonCC++JavaRBash+97
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RA

Reza Anvari

Screened

Junior Robotics Software Developer specializing in embedded systems and ROS2

Toronto, Ontario1y exp
Patagona TechnologiesToronto Metropolitan University

“Robotics engineer who built an educational/research robotic arm end-to-end, including IK/FK math, simulation-based validation, and ROS2 Humble integration with multiple teleoperation inputs (DualSense and Leap Motion). Also optimized a resource-constrained ESP32-S3 wireless maze robot to stream real-time video and sensor data over WiFi using TCP/HTTP with RTOS-based concurrency and binary struct packing.”

CC++PythonC#.NETGit+88
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SP

Sarang Pratham

Screened

Junior Software Engineer specializing in data engineering and GenAI

Kundapur, India3y exp
Abilitystack IncMoodlakatte Institute of Technology

“Built and deployed a production LLM-powered recruitment chatbot that automates key recruiting steps (sourcing, candidate engagement, screening). Strong in agent orchestration with LangGraph, including guided graph-based workflows, context-aware routing, and reliability measures like clarifying steps plus human-in-the-loop evaluation.”

PythonSQLStreamlitNoSQLApache SparkPySpark+58
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AA

Aldrin Azucena

Screened

Mid-level Full-Stack Software Developer specializing in web apps, CI/CD, and cloud infrastructure

Lethbridge, Alberta, Canada4y exp
Interfaith Food BankUniversity of Lethbridge

“Frontend engineer (~4 years) who led an admin dashboard for potato farmers end-to-end, integrating real-time and historical weather data to drive disease-severity predictions. Built scientifically validated calculation pipelines (FAO Penman-Monteith, late blight models), rigorous Cypress/unit testing, and print/PDF-ready reporting, while optimizing performance and API load with debouncing, caching, and feature-flagged rollouts.”

Visual Studio CodeTypeScriptJavaScriptGitGitHubBitbucket+94
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