Vetted Generative AI Professionals

Pre-screened and vetted.

PK

Senior Data Engineer specializing in multi-cloud data platforms and generative AI

Weston, FL5y exp
UKGUniversity of Alabama at Birmingham
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TL

Senior Software Engineer specializing in ML/AI and scalable data platforms

San Jose, CA11y exp
LabelboxNational University of Singapore
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YR

Mid-level AI/ML Developer specializing in FinTech fraud detection and GenAI assistants

MO, USA4y exp
Edward JonesUniversity of Central Missouri
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JF

Mid-level AI/ML Software Engineer specializing in Generative AI and NLP

Remote5y exp
EmerjenceBoston University
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MR

Executive product and technology leader specializing in AI, data platforms, and cloud transformation

Los Angeles, CA17y exp
Smart Tech Analytics GroupArkansas State University
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SD

Srijan Dokania

Screened ReferencesModerate rec.

Junior Robotics & Machine Learning Engineer specializing in perception, SLAM, and edge AI

Boston, MA2y exp
Field Robotics Lab (Northeastern University)Northeastern University

Built and deployed an Azure-based, fine-tuned CLIP visual retrieval system at Staples for a ~300k-item product catalog, improving edge-case recall by 12% by engineering a custom delta-similarity/dynamic-margin loss. Also has robotics experience using ROS2 for sensor/compute orchestration, including GPS-time-synchronized sensor triggering for robot swarms and latency-bounded optical-flow benchmarking for edge deployment.

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NH

Nabil Hamid

Screened ReferencesStrong rec.

Staff Full-Stack Software Engineer specializing in Healthcare and Retail web apps

San Francisco, CA11y exp
AccentureSan Francisco State University

Healthcare-focused software engineer/lead who has delivered customer-facing portals and internal call-center tools, including rebuilding a legacy Adobe Flash call center app into a modern TypeScript frontend with NgRx state management. Experienced leading onshore/offshore teams, integrating healthcare APIs, and driving adoption by visiting call centers to capture user workflows and bake them into regression testing—work that proved especially valuable during COVID-era shifts to video appointments.

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KP

Krishnapriyanka Ponnaganti

Screened ReferencesStrong rec.

Mid-level AI/ML Engineer specializing in agentic AI and production ML systems

Atlanta, GA4y exp
KKRGENAI Innovations LLCUC San Diego

ML/AI engineer with hands-on experience shipping production computer vision and GenAI systems, including a fabric defect detection platform that combined vision models with agentic LLM workflows to reach 89% human-inspector agreement at 200 ms latency. Also built a RAG-based code QA tool for developers and emphasizes production monitoring, evaluation, caching, and reusable Python service design.

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Rob Wlaschin - Director-level Engineering Manager specializing in AI platforms, FinTech, and Healthtech in Santa Clara, CA

Rob Wlaschin

Screened ReferencesStrong rec.

Director-level Engineering Manager specializing in AI platforms, FinTech, and Healthtech

Santa Clara, CA24y exp
Tifton PartnersCalifornia State University, Fresno

Serial entrepreneur building three distinct products: a context-aware AI chatbot, a connected TV companion-screen platform with an implementation client, and gamerogue.net, a mobile-optimized web-based virtual tabletop marketplace currently seeking funding. Brings hands-on fundraising experience, familiarity with the VC/accelerator ecosystem including YC, and a notably pragmatic approach to validating ideas based on existing market demand rather than speculative adoption.

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VV

Vaishnavi Veerkumar

Screened ReferencesStrong rec.

Mid-level AI Engineer specializing in GenAI and RAG systems

Boston, MA4y exp
VizitNortheastern University

AI engineer who built a production e-commerce system that analyzes product images alongside sales and demographic data to generate actionable creative recommendations, now used by 20+ clients. Also built orchestrated document/agent pipelines (Airflow, LangGraph) including a compliance drift detector auditing 401 compliance documents, with an emphasis on traceability, logging, and production integration.

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VK

Vamsi Krishna Chigurupati

Screened ReferencesModerate rec.

Mid-level Full-Stack Developer specializing in FinTech microservices

USA4y exp
CitigroupUniversity of Alabama at Birmingham

Backend engineer currently at Citigroup working on real-time transaction processing systems with Kafka. Stands out for using AI tools pragmatically in a regulated banking environment to improve debugging, testing, and developer productivity while keeping human control over architecture, security, and performance decisions.

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HD

HimavardhanReddy Donuru

Screened ReferencesModerate rec.

Senior Front-End/UI Lead specializing in enterprise web applications

Austin, TX10y exp
VerizonJawaharlal Nehru Technological University, Hyderabad

Frontend/UI lead with enterprise-scale experience on Verizon's vendor portal, a complex workflow system for fiber infrastructure contracts used by vendors, inspectors, and managers. He combines React micro-frontend architecture, TypeScript, and UX optimization to streamline demanding operational workflows, including reducing contract turnaround time from one week to two days and improving power-user efficiency with keyboard shortcuts and copy interactions.

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AG

Alpen Gandhi

Screened ReferencesStrong rec.

Executive LNG & natural gas commercial leader specializing in global energy trading

New Jersey, USA30y exp
QatarEnergy Trading

Commercial LNG/gas leader with hands-on experience spanning origination, commercial operations, business development, and regional marketing in India’s regasification market. Stands out for combining market creation, complex energy logistics strategy, and regulatory/commercial execution—including saving over US$25M in import tax through customs advocacy and structuring multi-party LNG/terminal agreements while managing PE risk.

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ST

Mid-level AI/ML Engineer specializing in GenAI and predictive modeling

Fullerton, California5y exp
UnitedHealth GroupGeorge Washington University

Built and deployed a GPT-4-powered medical assistant for clinical staff to reduce time spent searching guidelines and EHR information, with a strong emphasis on safety and compliance. Uses strict RAG, confidence thresholds, and fallback behaviors to prevent hallucinations, and runs production-grade workflows orchestrated with LangChain/LangGraph plus Docker/Kubernetes/MLflow and monitoring for reliability and cost.

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VK

Vamsi Koppala

Screened

Mid-level Machine Learning Engineer specializing in Generative AI and RAG systems

Barrington, IL4y exp
ComericaTexas Tech University

LLM/ML engineer who has shipped an enterprise RAG-based Q&A system (LangChain/LlamaIndex, FAISS + Azure Cognitive Search, GPT-3.5/4 via OpenAI/Azure OpenAI) to production on Docker + Kubernetes/OpenShift, tackling hallucinations, retrieval quality, latency/cost, and RBAC/IAM security. Also partnered with operations leaders to turn manual reporting into an LLM-powered summarization and forecasting dashboard driven by real KPIs and iterative stakeholder feedback.

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JM

Jose Moreno

Screened

Senior Growth Marketer specializing in paid acquisition and performance creative testing

Santa Monica, CA6y exp
Universal Music GroupSeton Hall University

Growth creative lead with hands-on experience running end-to-end paid creative tests for major music/entertainment campaigns at UMG, including a vinyl sale push that cut CPA by 20%+ in a tight promo window. Known for a modular ad-building approach (hooks/value prop/proof/CTA) and platform-native optimization across Meta, TikTok, and YouTube, plus strong label/creative-team alignment and QA discipline (including tracking).

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SK

Mid-level AI/ML Engineer specializing in Generative AI and healthcare data

NJ, USA6y exp
Johnson & JohnsonWichita State University

Built and deployed a production RAG-based document Q&A system on Azure OpenAI to help business teams search thousands of PDFs/Word files, using Qdrant vector search, MongoDB, and a Flask API. Demonstrates strong production engineering (streaming large-file ingestion, parallel preprocessing, monitoring/retries) plus systematic prompt/embedding/chunking experimentation to improve accuracy and reduce hallucinations, and has hands-on orchestration experience with ADF/Airflow/Databricks/Synapse.

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AN

Alex Nguyen

Screened

Junior Applied AI Engineer specializing in LLMs, RAG, and agentic systems

La Jolla, CA2y exp
Uniwise.aiUC San Diego

Co-founded a healthcare AI startup building and deploying software directly with end users, emphasizing rapid shipping, deep user interviews, and workflow-first adoption. Has hands-on production deployment experience on AWS (including diagnosing a silent AWS App Runner failure caused by an ARM vs amd64 Docker build mismatch) and is motivated by customer-facing, travel-heavy roles to keep engineering tightly connected to real-world usage.

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AR

Anurag Reddy

Screened

Mid-level Data Scientist specializing in ML, MLOps, and Generative AI

TX, USA5y exp
CaterpillarUniversity of Illinois Chicago

ML/NLP engineer who built a RAG-based technical assistant for Caterpillar field engineers, transforming PDF keyword search into intent-based semantic retrieval across manuals, logs, sensor reports, and technician notes. Strong in productionizing data/ML systems (Airflow, PySpark) with rigorous preprocessing, entity resolution, and evaluation—delivering measurable gains in accuracy, relevance, and duplicate reduction.

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SV

Mid-Level Software Engineer specializing in full-stack, AI/LLMs, and Android

Plano, TX4y exp
L&T Technology ServicesUniversity of Texas at Austin

Backend/AI engineer who built a Spring Boot timesheet API on AWS (Postgres, Docker, Nginx) used by hundreds of daily users and resolved severe deadline-driven latency/5XX incidents via query optimization, connection pool tuning, and Redis caching. Also shipped application-layer LLM features (Mistral + LangChain chatbot) and designed a Planner/Executor/Verifier troubleshooting agent with verification-based guardrails to prevent hallucinated root-cause analyses.

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RP

Rubesh Phaiju

Screened

Senior Full-Stack Java Engineer specializing in cloud-native microservices and GenAI

Mechanicsburg, PA8y exp
DeloitteUniversity of the Cumberlands

Deloitte engineer who built and shipped AI-powered, Kafka-driven workflow automation for transportation/document processing, including LLM-based semantic search. Strong in production reliability (idempotency, offset management, retries), observability (Datadog/CloudWatch), and database performance tuning (PostgreSQL/Flyway), with measurable latency improvements.

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MB

Manish Birla

Screened

Executive Program & Engineering Leader specializing in digital transformation and SaaS platforms

San Ramon, CA26y exp
LEAP AI TechnologiesSavitribai Phule Pune University

Cross-functional product/engineering leader with startup and enterprise experience (Whimstay, Wells Fargo, Leap AI Technologies). Has owned end-to-end delivery including UI and payment architecture—built a multi-customer reservation payment flow using pre-auth plus event/timer-driven reminders and handled tricky edge cases like date changeover. Also introduced lightweight process (Jira, sprints, team/module structuring) to increase delivery speed in an early-stage AI document-matching startup.

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Cristian Vega - Senior AI/ML Engineer specializing in Generative AI and RAG in California, null

Cristian Vega

Screened

Senior AI/ML Engineer specializing in Generative AI and RAG

California, null9y exp
Morf HealthUniversity of Texas at Austin

ML/NLP practitioner at Morf Health focused on unifying fragmented healthcare data by linking structured patient/encounter records with unstructured clinical notes. Has hands-on experience with transformer embeddings, vector databases, and domain fine-tuning, plus rigorous evaluation (precision/recall) and human-in-the-loop validation with clinical SMEs to make pipelines production-grade.

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