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Shreya Tumati
Shreya is a generative AI engineer with experience designing and deploying production-grade AI systems across insurance, healthcare, and financial services. Focusing on end-to-end GenAI solutions, Shreya builds retrieval-augmented generation (RAG) pipelines, fine-tunes large language models, and develops autonomous agents. She also architects cloud-native AI platforms on AWS, Azure, and Google Cloud Platform (GCP) to ensure scalability, reliability, and operational efficiency.
Show MoreIshita Mukherjee
At Royal Bank of Canada, Ishita led the architecture and delivery of an enterprise agentic AI platform supporting 100+ business users. She is a principal engineer and architect with over 15 years of experience in data and AI/ML for financial services and healthcare. Ishita's expertise spans AWS, Databricks, and Python; she reduced infrastructure costs by 60% while at RBC.
Show MoreYung Chi Daniel Cho
Daniel (Yung Chi) is a senior AI and machine learning engineer with over seven years of experience in production ML systems, LLM evaluation, and ML infrastructure. His expertise spans LangChain, Spark, and PyTorch for the travel and manufacturing industries. At Expedia, Daniel (Yung Chi) led evaluation design for an agentic trip-planning product, defining a custom rubric with 30+ metrics.
Show MoreCaio Vitor Oliveira Moreira
Caio has spent over 10 years building production-grade AI and data systems across fintech and healthtech. His toolkit centers on Python, LangChain, and AWS Bedrock. While at NVIDIA, Caio rebuilt executive dashboards for capacity planning and cut reporting time by 40%.
Show MoreMouad Hamri
Mouad is an AI, machine learning, and data architect with more than 19 years of experience, specializing in agentic AI systems and large-scale data architectures. He has designed and deployed enterprise-grade LLM platforms, RAG pipelines, and autonomous AI agents using LangChain, LangGraph, and self-hosted models. Holding a PhD in artificial intelligence, Mouad delivers proven expertise across Azure, MLOps, and cloud-native stacks in enterprise environments.
Show MoreDaniil Volobuiev
Daniil is a Python back-end engineer with 3+ years of experience building production APIs, data pipelines, and AI integrations for clients such as Jellyfish, Actionable, and Atomaze. His primary expertise is in FastAPI, LangChain, and Celery for B2B SaaS products, where Daniil thrives in delivering practical solutions with clean architecture and measurable outcomes. He reduced LLM token consumption by 40% while at Jellyfish.
Show MoreAdrian Marcu
Adrian is a senior full-stack software engineer with over 10 years of expertise. He has specialized in Java, Spring Boot, React, and cloud technologies spanning AWS, GCP, and Azure. Adrian leverages Python, LangChain, Next.js, and TypeScript to build AI-powered, scalable solutions for startups and enterprises.
Show MoreBurcin Sarac
Burcin is a principal AI architect and data scientist with 10+ years of experience. He specializes in large language models (LLMs), agentic AI systems, and end-to-end MLOps, with deep expertise across the Python ML ecosystem, LangChain/LangGraph, and RAG architectures. Burcin designs and ships production-grade AI products across all three major clouds—GCP, Azure, and AWS—from multi-agent conversational systems to cloud intelligence platforms for finance, eCommerce, FMCG, and SaaS clients.
Show MoreGaga Lobjanidze
Gaga is a Microsoft Certified Azure Solutions Architect and senior AI engineer with 10+ years of experience designing large-scale distributed systems. He specializes in orchestrating LLMs using LangChain and LangGraph, backed by proficiency in Python, C#/.NET, and Java. Gaga leverages algorithms and SOLID principles to build secure, autonomous AI solutions capable of handling massive throughput.
Show MoreFahad Murtaza
Fahad is a software engineer with 23+ years of experience, now specializing in AI/ML and agentic systems. He trains and evaluates AI coding agents for frontier AI labs and ships production LLM products: MCP tool servers, RAG pipelines (LangChain, Pinecone), and ML ensembles. His foundations span Python (Django, FastAPI), Rust microservices, Go, and Node.js on AWS and Kubernetes, with deep expertise across proptech, fintech, edtech, and legaltech.
Show MoreHaveela Karre
Haveela is a data scientist with three years of experience developing AI-driven solutions that transform data into actionable insights. She specializes in machine learning (ML), large language models (LLM), and predictive analytics and has made impactful contributions at Mavvrik.ai, Turing, and Tredence Inc. Haveela's work drives data innovation and enhances business intelligence.
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