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Vetted SQL Professionals

Pre-screened and vetted.

SQLPythonDockerCI/CDAWSGit
PM

Pranav Marla

Screened

Mid-level AI/ML & Full-Stack Engineer specializing in LLM agents and generative AI

Dallas, United States5y exp
KalpaNortheastern University

“LLM/agent builder who shipped a live consumer AI-agent app (kalpa.chat) that visualizes complex reasoning as interactive graphs and abstracts multi-provider model usage via a unified wallet. Professionally has applied LangChain/LangGraph to IVR parsing and to scaling a football video-generation pipeline at DAZN, including shipping a VAR-specific retrieval/order fix via SQL after iterating with a non-technical PM.”

PythonJavaC++JavaScriptTypeScriptSQL+80
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GH

Girum Hagos

Screened

Senior Front-End Developer specializing in React/Angular and cloud-native healthcare apps

Toronto, ON6y exp
MediResourceUdacity

“Senior/Lead Frontend/Full-Stack engineer in Toronto with proven experience shipping high-stakes, real-time and regulated products across healthcare, legal/compliance, and fintech. Built a real-time compliance dashboard that survived a 400% data spike and a no-code workflow builder supporting 500+ nodes, with strong emphasis on performance engineering, type-safe architecture, and automated quality/rollout practices.”

.NETAngularAWSAPI DesignAzure DevOpsCI/CD+113
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BP

Bilal P. Mohamed

Screened

Senior Unity/XR Developer specializing in AR/VR and AWS-backed real-time experiences

London, UK10y exp
Eugene’s ARUniversity of East Anglia

“Unity XR developer who has shipped multiple Meta Quest apps, including an NHS medical training VR simulation where realistic, consultant-validated interaction mechanics and highly configurable systems were critical. Also built and shipped a solo indie AR product ("Eugene's AR Wiki") end-to-end, supporting a wide range of iOS/Android devices and incorporating analytics, interactive content, and engagement features like word games and face filters.”

UnityUnreal EngineC#PythonJavaScriptC+++81
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AK

Aditya Kulkarni

Screened

Mid-Level Full-Stack Software Engineer specializing in cloud-native and mobile applications

NY, USA4y exp
Spresso.aiSan José State University

“LLM-focused engineer with end-to-end experience shipping an OpenAI-powered edtech teacher assistant into production, using Humanloop-driven prompt iteration, rigorous observability (Datadog), and A/B testing tied to real learning metrics (25% comprehension lift). Also led adoption-driving technical demos at SiriusXM (event-driven AWS Lambda/Kotlin/CDK pipeline cutting processing from 24 hours to seconds) and partnered with sales at Spresso.ai to close eCommerce SDK deals and boost activation from 40% to 85%.”

AgileAndroidAWSAWS LambdaCC+++93
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MY

Manvitha Yeeli

Screened

Mid-Level Full-Stack Software Engineer specializing in React and Node.js

Remote, USA4y exp
One CommunityUniversity of Alabama at Birmingham

“Built and owned end-to-end TypeScript/React dashboards with a Node.js backend, including post-launch additions like role-based access and new reporting views enabled by modular architecture and clean API boundaries. Also created an internal real-time operations/engineering dashboard that replaced spreadsheets and reduced manual tracking, iterating quickly based on direct team feedback.”

JavaCC++JavaScriptPythonTypeScript+77
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SK

sai keerthana peepalpati

Screened

Mid-level .NET Backend Developer specializing in secure APIs and enterprise integrations

Boston, MA5y exp
Transform LabsJawaharlal Nehru Technological University, Hyderabad

“Built and owned UPS tracking/reporting and operations workflow dashboards, delivering customer-facing APIs and real-time React/TypeScript UIs backed by .NET Core. Experienced in high-volume microservices using IBM MQ/Azure Service Bus with strong reliability patterns (idempotency, retries, DLQ) and Azure-based observability, plus performance tuning across frontend and SQL-backed services.”

C#.NETMicroservicesNode.jsAngularReact+157
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MS

Manoj Saddanapu

Screened

Mid-level Full-Stack Software Engineer specializing in Java/Spring Boot, React, and cloud

United States4y exp
SubaruCentral Michigan University

“Backend/platform engineer who built real-time connected-vehicle telemetry analytics at Subaru, spanning Kafka streaming, Python/FastAPI ETL, and low-latency WebSocket delivery (minutes to <2s). Strong Kubernetes + GitOps practitioner across AWS EKS and Azure AKS (Helm, ArgoCD, Jenkins/GitLab) and has led major on-prem-to-cloud migrations for financial microservices using Terraform and AWS DMS with measurable cost and reliability gains.”

JavaPythonReactReduxNode.jsAngularJS+141
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HK

Harika Kandregula

Screened

Mid-Level Full-Stack .NET Developer specializing in cloud-native microservices and AI integration

Orlando, FL4y exp
State of FloridaFlorida International University

“Software engineer with hands-on experience building and maintaining a React accessibility utility/component library (open-source-style) used across university portals, emphasizing WCAG 2.2 compliance, robust focus/keyboard behavior, and Jest/React Testing Library coverage. Also built and maintained .NET Core microservices at the Florida Department of Transportation, including integrating AI-driven features, with strong ownership around observability, incident response, and performance-focused refactoring.”

AgileAlgorithmsAmazon CloudWatchAmazon DynamoDBAmazon EC2Amazon S3+156
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YS

Yash Sanap

Screened

Junior Data Scientist specializing in ML, geospatial analytics, and LLM applications

Virginia Beach, VA2y exp
City of Virginia BeachGeorge Mason University

“Built and deployed a production AI “term explainer” agent that adapts explanations to beginner/intermediate/expert users by combining multi-step LLM reasoning with grounded Wikipedia retrieval. Owns end-to-end agent orchestration (smolagents/Python), reliability patterns (fallback across LLM providers, retries, guardrails), and observability/metrics-driven evaluation; also partnered with a non-technical researcher to deliver a plain-language research assistant agent.”

PythonSQLJavaGoBashJavaScript+95
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AZ

Abdelrahman Zeidan

Screened

Mid-Level Software Engineer specializing in Generative AI and LLM applications

Johnston, Iowa4y exp
CortevaNortheastern University

“Built and deployed a production RAG-based AI assistant for sales reps to unify access to product info, pricing, and internal documents across multiple systems. Implemented ETL pipelines for normalization/chunking/embeddings, integrated the assistant into internal React/TypeScript UIs with user-specific context, and enforced security with private vector storage and permission-filtered retrieval.”

AgileAmazon EC2Amazon S3Amazon SageMakerAngularAPI Development+73
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DK

Deepak K

Screened

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

Overland Park, KS4y exp
IntuitUniversity of Central Missouri

“ML/LLM engineer with production experience building a compliant RAG-based virtual assistant at Intuit, optimizing embeddings and FAISS retrieval (including PCA) for low-latency, privacy-controlled search and deploying via AWS SageMaker containers. Also built scalable Airflow+MLflow pipelines using Docker and KubernetesExecutor, cutting training cycles by 37%, and partnered with civil engineers/project managers at Aegis Infra to deliver predictive maintenance for construction equipment.”

A/B TestingAmazon AthenaAmazon EC2Amazon S3BERTCI/CD+93
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TP

Thilak P

Screened

Mid-level Data Engineer specializing in cloud ETL/ELT and big data pipelines

5y exp
W. R. BerkleySacred Heart University

“Backend/data engineer who builds Python (FastAPI) data-processing API services for internal analytics/reporting, emphasizing modular architecture, async performance tuning, and reliability patterns (health checks, retries, observability). Also migrated legacy on-prem ETL pipelines to Azure using ADF/Data Lake/Functions and implemented a near-real-time ingestion flow with Event Hubs plus watermarking to handle late events and deduplication.”

PythonSQLRCHTMLCSS+153
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RP

Rupesh Pathak

Screened

Junior Data Scientist and Robotics Perception Engineer specializing in GenAI and autonomous systems

Boston, MA2y exp
VERIDIX AINortheastern University

“Robotics software architect who built an automated pick-and-place palletizing prototype at BLACK-I-ROBOTICS, spanning perception (multi-RealSense fusion, segmentation, 6D pose, ICP), GPU-accelerated motion planning (MoveIt 2 + NVIDIA CuRobo), grasp generation, and safety (human detection + safe mode). Also brings cloud/CI/CD depth from VERIDIX AI (AWS Cognito/Lambda/ECS and CodePipeline stack) and demonstrated strong debugging chops by reducing outdoor rover EKF drift to ~5 cm via Allan variance-based IMU tuning.”

PythonCC++MultithreadingSQLMATLAB+164
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AJ

Aman Jain

Screened

Mid-level Software Engineer specializing in cloud-native data pipelines and ML platforms

Boston, MA4y exp
Community Dreams FoundationBoston University

“Backend engineer who has owned end-to-end delivery of Python/FastAPI microservices for real-time data processing and alerting, including performance tuning (Postgres optimization, caching, async processing). Strong DevOps/GitOps background: Docker + Kubernetes deployments with GitHub Actions CI/CD and ArgoCD-driven GitOps, plus experience supporting phased on-prem to AWS migrations and building Kafka-based streaming pipelines.”

PythonJavaRCC++MySQL+101
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AR

Anthony Roberts

Screened

Senior Full-Stack Software Engineer specializing in web platforms and FinTech systems

Fairburn, GA17y exp
InsurepayUniversity of Canberra

“Full-stack engineer with ~20 years of experience (including 5–6 years in consultancy) who has shipped and operated production systems across a wide range of stacks. Recently owned an end-to-end receipts feature integrating Stripe, generating PDFs, and sending HTML emails, deployed via GitHub Flow to AWS ECS; handled real-world performance issues (oversized merchant images) with compression and server tuning.”

A/B TestingAgileAngularAWSBootstrapCI/CD+85
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YP

Yash Pankhania

Screened

Mid-level AI Engineer specializing in LLMs, RAG, and data engineering

Boston, MA5y exp
Humanitarians.AINortheastern University

“AI Engineer Co-Op at Northeastern University who built a production Patient Persona Chat Bot to help nursing students practice clinical interactions, fine-tuning Llama 3 and integrating a LangChain + Pinecone RAG pipeline deployed on Amazon Bedrock. Emphasizes clinical accuracy and reliability with guardrails, retrieval filtering, and continuous evaluation, and also brings strong data engineering/orchestration experience (Airflow, EMR/PySpark, ADF, dbt, Databricks, Snowflake).”

AgileAmazon BedrockAmazon DynamoDBAmazon EMRAmazon RDSAmazon Redshift+127
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KB

KUNAL BABBAR

Screened

Mid-level Full-Stack Engineer specializing in AWS serverless and secure web applications

5y exp
Juego.JuegosNJIT

“JavaScript full-stack engineer with experience at EY building secure, cloud-ready React/Node.js applications on AWS and currently at startup Juego Juegos owning the AWS backend and CI/CD via AWS Amplify. Demonstrated impact through performance tuning of a React analytics dashboard (reduced initial load time ~20%) and resolving real payment failures by debugging Stripe 3DS flows and updating AWS Lambda plus frontend error handling.”

Amazon DynamoDBAmazon EC2Amazon RedshiftAmazon RDSAmazon S3Amazon SNS+96
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LR

Likhith Ramesh

Screened

Mid-level Full-Stack/Backend Java Developer specializing in IAM and microservices

Tucson, Arizona3y exp
CognizantUniversity of Arizona

“Full-stack Java developer (~4 years) who built a telecom asset management system end-to-end with React and Spring Boot, and led/participated heavily in migrating it from a monolith to Spring Cloud-based microservices. Experienced with high-volume, data-driven workloads using Kafka (partitioning, batching, resilient consumers) and production observability via centralized logging with ELK and Splunk.”

AgileAmazon DynamoDBAmazon RDSAWSAWS LambdaAngular+97
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KR

Krishna Rajput

Screened

Mid-level AI Engineer & Data Scientist specializing in LLMs, RAG, and multimodal systems

Tempe, AZ5y exp
HCLTechArizona State University

“LLM/GenAI engineer who built a production AI-powered credit risk policy summarization and compliance alerting platform at HCL Tech, focused on factual accuracy and auditability for a financial client. Implemented a multi-retriever LangChain RAG architecture with citations-only prompting, fallback agents, and human-in-the-loop legal review—cutting manual review time by 35% and scaling to 12 teams.”

A/B TestingAI AgentsAnomaly DetectionAWS GlueAWS LambdaAzure Machine Learning+126
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NB

nitesh bommisetty

Screened

Mid-level Data Scientist specializing in ML, NLP, and LLM-powered solutions

Tampa, FL4y exp
LumenUniversity of South Florida

“AI/NLP-focused practitioner who built a zero-/few-shot LLM event extraction system on the long-tail Maven dataset, combining prompt-structured outputs with LoRA/QLoRA fine-tuning and rigorous F1 evaluation. Also implemented entity resolution/data cleaning pipelines and embedding-based semantic search using Sentence-BERT + FAISS, and has healthcare experience delivering a multilingual speech/translation mobile prototype using HIPAA-compliant Azure Cognitive Services.”

PythonRSQLTensorFlowPyTorchKeras+123
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GG

Gabriele Gobbi

Screened

Mid-level Data Scientist specializing in GenAI, LLM-to-SQL, and analytics platforms

Turin, Italy3y exp
Engineering Ingegneria InformaticaUniversity of Ferrara

“LLM/agentic AI builder who led end-to-end integration of an LLM system into a business intelligence product, creating a scalable, metadata-driven RAG/agent pipeline with an orchestrator that routes queries to specialized agents (including DB-backed quantitative querying). Also built an LLM-to-SQL chatbot and partnered with non-technical stakeholders to capture domain context and improve SQL generation, using automated LLM-based testing to evaluate reliability.”

PythonMachine LearningScikit-LearnTensorFlowPyTorchLarge Language Models (LLMs)+51
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DP

Drashti Patel

Screened

Junior Software Engineer and ML Researcher specializing in full-stack and applied deep learning

Indiana, USA3y exp
Purdue UniversityPurdue University

“LLM engineer who built a production-style educational questionnaire generation system (MCQs/fill-in-the-blanks/short answers) using Hugging Face models (BERT/T5) and implemented grounding, decoding tuning, and post-generation validation to control hallucinations and quality. Also developed a "tech care" assistant chatbot with a custom Python orchestration/router layer (intent classification, context management, multi-step flows) and a structured testing/evaluation approach including expert review and automated checks.”

PythonCC++HTMLCSSJavaScript+98
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IV

Indraneel V

Screened

Mid-level Cloud & DevOps Engineer specializing in AWS/Azure, Kubernetes, Terraform, and CI/CD

Griffin, GA8y exp
ZSAuburn University at Montgomery

“IBM Power/AIX infrastructure engineer with hands-on production experience across Power8/Power9 frames, VIOS and HMC, including resolving a production LPAR outage caused by vFC mapping issues. Has operated PowerHA clusters for critical finance workloads, running quarterly failover tests and handling an unplanned failover triggered by a network adapter failure, then improving resilience with redundancy and monitoring automation.”

Amazon EC2Amazon EKSAmazon S3Amazon RDSAWS IAMAmazon VPC+115
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LO

Landry Ottou

Screened

Mid-level DevOps/Cloud Engineer specializing in multi-cloud CI/CD and Kubernetes

Miami, FL3y exp
Royal CaribbeanGeorgia State University

“IBM Power/AIX infrastructure engineer who has owned a sizable production estate (50 Power servers / ~200 LPARs) spanning VIOS/HMC, SAN/NFS, and PowerHA clusters. Demonstrates strong incident leadership (LPAR outage + split-brain recovery) and a process-improvement mindset with measurable reductions in recurrence/MTTR, while also bringing modern DevOps/IaC experience (Jenkins, ArgoCD, Terraform, security scanning, canary/blue-green).”

.NETAgileAnsibleAWSAzure DevOpsAzure Monitor+110
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