Multi-Agent Generative AI Build

@sajjadtaghvaeifr

Hello, I trust you're doing well. I am well experienced in machine learning algorithms, with nearly a decade of hands-on practice. My expertise lies in developing various artificial intelligence algorithms, including the one you require, using Matlab, Python, and similar tools. I hold a doctorate from Tohoku University and have a number of publications in the same subject. My portfolio, which showcases my past work, is available for your review. Your project piqued my interest, and I would be delighted to be part of it. Let's connect to discuss in detail. Warm regards. please check my portfolio link: https://www.freelancer.com/u/sajjadtaghvaeifr

@pkundu25

I am an experienced IT Professional/AI Developer. Your job caught my eye and looks to be quite interesting to me as I developed varieties of AI Agent and Agentic AI systems in recent past. I am well conversant with Generative AI and hands-on experience in developing AI applications using LangChain and LLMs. I am a career coach in AI/ML, and I am confident that I will be able to help you by developing multi-agent GenAI systems capable of reasoning and planning using standard frameworks like LangGraph. Similar work done in the past: - AI Agent for Risk and Mitigation - AI Powered Copilot for Text2SQL Query - Document segmentation using Agentic AI - Customer Support Assistant - Semantic Search Engine Relevant Skills: - Python - Agentic AI - LangGraph/CrewAI/n8n - GPT4o/Gemini/Llama3.2/Mistral - AWS/Thunder Compute - MySQL/PostgreSQL - TensorFlow/PyTorch - Google Colab - OpenCV Let's have a chat to understand the project objective and other relevant details. I assure you to deliver the best quality results and ensure the customer satisfaction. Looking forward to hearing from you soon. Thanks for the opportunity.

@pinkeegupta

Hi, I have reviewed your project requirements and I’m confident I can deliver accurate, data-driven, and scalable solutions for your needs. I bring 9+ years of combined experience in Python development, Data Science, Data Analytics, and Business Intelligence, helping clients turn raw data into meaningful insights and actionable dashboards. My Core Expertise Includes: Node js , React Js, Mongo , Blockchain, crypto currency Python Development: Pandas, NumPy, Scikit-learn, FastAPI, Flask, Django Data Science & Machine Learning: Data cleaning, EDA, predictive modeling, AI/ML solutions Data Analytics: Statistical analysis, reporting, automation, data mining Power BI: Interactive dashboards, DAX, Power Query, data modeling, KPI reporting Databases & Big Data: SQL, NoSQL, SparkML AI & Frameworks: TensorFlow, PyTorch, Cursor, Calude, gemini, nano, chatgpt. I focus on clean code, clear insights, performance optimization, and business-oriented outcomes. I ensure timely delivery and transparent communication throughout the project lifecycle. Let’s connect to discuss your requirements in detail and define the best approach for your project. Looking forward to working with you. Regards, Anju Logical Soft Tech Pvt Ltd, Indore(M.P)

@AhmadXpert2410

Hi there, Your requirement calls for someone who can bridge advanced AI research concepts with production-grade engineering, particularly across Generative AI, RAG systems, and agentic workflows. As a Data Scientist actively working on AI-driven systems, I have hands-on experience with LLM integrations, prompt engineering, workflow orchestration, and scalable AI solution design involving OpenAI ecosystems, vector retrieval pipelines, and automation-centric architectures. I can contribute strongly across the full GenAI lifecycle, including retrieval-augmented generation pipelines, multi-agent orchestration patterns, backend API integration, model interaction workflows, and cloud-ready deployment strategies. My work has involved Python-based AI engineering using frameworks and tooling around LLM applications, data pipelines, semantic search systems, and AI-assisted automation, with focus on maintainability, performance, and production reliability rather than experimental prototypes alone. What stands out in your requirement is the need for practical engineering leadership alongside technical depth, especially in rapidly evolving AI environments. I approach projects with emphasis on scalable architecture, clean implementation, structured experimentation, and clear collaboration so solutions remain extensible as models, tools, and business requirements evolve over time. Regards, Ahmad

@KrisuTechkul

Hi, we are a team of 20+ AI/ML Engineers based in Delhi - have completed 300+ projects with 100% client satisfaction & long term association. Drawing from extensive experience in AI and ML leadership, focusing on generative AI, combined with a practical background in building multi-agent systems, I believe I am uniquely qualified for this project. With proficiency in Python and versatile knowledge of ML libraries like PyTorch and TensorFlow, I have successfully navigated open-source LLMs (e.g., LLaMA) and proprietary platforms/APIs (e.g., OpenAI GPT), much like the ones highlighted in the project description. Moreover, my grasp of cloud-based AI platforms such as Vertex AI and SageMaker aligns well with the project's cloud-native focus. I am no stranger to deploying Docker or serverless architectures alongside managed cloud services. Additionally, my backend engineering expertise enables seamless integration of AI models into your existing infrastructure. My comprehensive skill set extends to SQL (e.g., PostgreSQL) and NoSQL (e.g., DynamoDB) databases, empowering me to meet your data storage and retrieval requirements, essential for any ML project. Partnering with you would not just fulfill your immediate requirement but would also set a strong foundation for future collaboration.

@akkiwadhwa1995

I have strong experience building scalable AI-powered data platforms, automation systems, and LLM-based workflows using Python and cloud-native architectures. My recent work includes large-scale data pipelines, AI enrichment systems, and automation platforms processing millions of records daily. My experience includes: Generative AI applications using OpenAI/Gemini APIs RAG pipelines & prompt engineering Multi-agent workflows & automation systems Python backend development Data extraction, normalization & AI enrichment Scalable APIs and cloud deployments Dockerized services and distributed processing I’m comfortable working with: LangChain / agentic workflows OpenAI, Gemini, and open-source LLMs PostgreSQL & NoSQL databases FastAPI, Flask, and backend systems AI-driven automation and reporting systems I can contribute across architecture, backend engineering, AI workflow implementation, and scalable production deployment.

@chiragardeshna

Hi there, Strong alignment with this project comes from experience building enterprise-grade Generative AI platforms with multi-agent orchestration, RAG pipelines, LLM integrations, and scalable cloud-native AI architectures. Clear understanding of the requirement to design and develop advanced multi-agent AI systems with reasoning workflows, prompt engineering, model orchestration, retrieval systems, and scalable backend infrastructure using modern AI frameworks. Hands-on expertise with Python, LangChain, LangGraph, CrewAI, OpenAI, Gemini, LLaMA, Mistral, PyTorch, TensorFlow, vector databases, cloud AI services, and scalable API engineering ensures reliable and production-ready implementation. Risk is minimized through modular agent architecture, structured RAG evaluation, scalable deployment planning, secure API orchestration, model performance validation, and clean documentation for long-term maintainability. Available to start immediately happy to discuss architecture recommendations, delivery roadmap, and next steps. Recent work: https://www.freelancer.com/u/chiragardeshna Regards Chirag

@Web1devloper

With over 8 years of comprehensive experience in data science, machine learning, and advanced Python programming, I am confident that I have the expertise required to fulfill your Multi-Agent Generative AI Project. One of my core skills is **Machine Learning**, which involves working with libraries like PyTorch and TensorFlow. As a data scientist, I am comfortable with models and platforms ranging from proprietary ones like OpenAI's GPT to open-source LLMs such as LLaMA For your preference for cloud AI platforms, my hands-on experience in major cloud platforms like Vertex AI would be an asset. Moreover, I understand the importance of smooth integration, even with sizeable datasets. Skills such as **SQL** and **NoSQL** - PostgreSQL and DynamoDB are fully at my disposal should we need to manipulate multiple databases. My expertise in backend engineering and working knowledge of Docker will also ensure that the system we build for you is scalable on cloud-native architecture. Lastly, my agile mindset and an ability to mentor engineers adaptively fuels innovation. Having catered to fast-changing environments previously, I can assure you of efficient management even amid challenging times. With me in your team, you can be assured of not only a streamlined process but focused impact.

@arundutt83

What exactly you are looking for? Mentoring or development applications as well. We can have discussion in detailed.

@manoval09

Hi, Your brief cuts off mid-sentence, so before going further — multi-agent systems built properly require clear scoping of agent roles, orchestration topology, and shared-state strategy, and those decisions drive the entire architecture. Getting that wrong early means expensive rewrites. For a system like this I'd use LangGraph as the orchestration layer, with each agent defined as a node in a stateful graph — this gives deterministic control flow over fully autonomous agents, which matters when you need auditability. Tool-calling agents get scoped permissions via function schemas, inter-agent communication flows through a typed shared state object, and I'd wire in structured logging from day one so you can trace exactly which agent made which decision and why. Before I commit to scope or timeline, I need the full project description — specifically: what do the individual agents need to do, what data sources do they hit, and is this greenfield or integrating into an existing codebase? The $400 budget also suggests this may be a scoped PoC rather than a production system — happy to discuss what's achievable at that price point versus what a production build actually requires. Best regards, Val

@usamaansari786

Cloud AI Platforms: Drawing from my experience with major cloud platforms like Vertex AI and SageMaker, I am confident in my ability to leverage their AI/ML services effectively for your project. With and Docker, serverless architectures, and managed cloud services. With a strong understanding of SQL (e.g., PostgreSQL) and NoSQL (e.g., DynamoDB) databases, I can ensure robust data management a crucial requirement for any AI project. Agile & Versatile Approach: My career has witnessed successful collaboration on agile projects and my multi-faceted skill set helps meet changing requirements effortlessly. The benefit from working in an environment is reflected in my ability to foresee project contingencies and adapt strategies accordingly to deliver high-performance systems. Warm Regards, Usama f

@dushyant317

We are a senior AI/ML engineering team with 10+ years of experience building production-grade Generative AI, RAG pipelines, and Agentic AI systems using frameworks like LangChain/LangGraph, Python-based ML stacks (PyTorch, TensorFlow, Scikit-learn), and cloud platforms such as AWS, Azure, and GCP, with strong expertise in LLM integration, backend APIs, and scalable cloud-native architectures.

@samyotechit

As an experienced AI/ML Engineer, specializing in building intelligent AI Agents and RAG-based systems, I am confident that I possess the requisite skills to deliver a high-end multi-agent generative AI solution for your project. Operating in the AI/ML space for over 8 years, my expertise in crafting and executing GenAI solutions, specifically in NLP and LLM architecture, is undisputed. Additionally, my extensive programming experience in Python, with strong understanding of open-source LLMs and proprietary platforms, perfectly aligns with your technical requirements. Moreover, I bring valuable experience in mentoring other engineers and working within agile, fast-paced environments to foster efficient delivery. I can leverage this to lead your team toward effectively realizing usage of frameworks such as Lang Chain or Lang Graph to build an optimized multi-agent reasoning system. In conclusion, by combining my proven track record of delivering innovative conversational AI products with your outlined priorities,I am ready to guarantee a solution that enhances customer interactions and automates internal processes harmoniously. Look no further for a diligent, experienced project partner who brings not just technical prowess but strategic vision too. Consider me committed to the legacy votrevious

@Geetam00

With over half a decade of experience as a dedicated full-stack developer, I've found my stride in building future-focused digital solutions that cater to the ambitious goals of various businesses. I specialize in designing and implementing scalable architectures, which will be invaluable for your Multi-Agent Generative AI project. Drawing from hands-on experience with AI/ML libraries like PyTorch and TensorFlow, along with open-source LLMs like LLaMA and Mistral, I offer a powerful combination of skills that align directly with your project description. What sets me apart? It's the personalized approach I bring to every unique project. This includes leveraging cloud-native systems with Docker, applying my strong API and backend engineering skills, working adeptly with SQL and NoSQL databases, and ensuring smooth integration across platforms like Vertex AI or SageMaker. Moreover, as a seasoned mentor, I find fluidity in agile environments - this means adaptability and keeping up with the pace of innovation is second nature to me. My dedication to quality and client satisfaction has consistently gained me trust in over 42 countries across 1000+ projects. If you choose me for this assignment, rest assured of not just professional expertise but also quick response time, round-the-clock support, complete fluency in English for effective communication, and perhaps most significantly.

@serviceaxisgroup

Hi, I can help with delivering a working multi-agent generative AI system that reasons, plans, and produces reliable outputs. I’ll start by designing agent roles, tools, and a minimal LLM workflow in Python using a framework like LangChain/LangGraph or CrewAI. I’ll reduce risk with a first RAG-backed prototype, clear prompt/guardrails, and logged tool/model calls for easy review. Which LLM/provider should we use (OpenAI, Gemini, Azure, or open-source)? Do you already have a RAG data source or should we build the pipeline from your documents?

@rakhshanz3

As an AI and ML expert with over a decade of experience, I believe I am the perfect fit for your Multi-Agent Generative AI Build project. My extensive background in Artificial Intelligence and Machine Learning Solutions as well as my strong Python expertise aligns directly with the task at hand. To emphasize a few relevant experiences, let me highlight my work as a Chief Technology Officer where I performed duties entailing the construction of GenAI tools for different purposes such as document processing, data extraction, recommendation systems, and workflow automation – very similar to what you require. Not to mention, my experience building scalable cloud-native systems using Docker and serverless architectures would come handy in deploying your solution in the cloud. In conclusion, my skills and experiences demonstrate my capability to deliver what you need for this project. I bring not only technical prowess but also an understanding of what it requires to work in agile, fast-changing environments. Together, we can build a remarkable Multi-Agent Generative AI that goes beyond expectations

@mykolas67

Hello. The difficult part in multi-agent GenAI systems usually isn’t getting agents to talk to each other, it’s preventing unstable reasoning loops, runaway token costs, inconsistent tool outputs, and state synchronization problems once real users start interacting with the system concurrently. For a production setup, I’d separate orchestration, memory, and tool execution layers early instead of letting agents directly manage shared state. I’d also avoid relying only on prompt chaining for business-critical logic. In most real deployments, deterministic validation and fallback handling become just as important as the LLM layer itself. For RAG, I’d focus heavily on retrieval quality and context-window control before considering fine-tuning. I’ve worked on AI workflow systems involving multi-step reasoning, document processing, OCR pipelines, and API-connected agent flows using Python, FastAPI, vector stores, and OpenAI/Gemini-based architectures I can help structure the agent architecture, tool routing, memory strategy, and deployment flow in a way that stays maintainable as the system grows. Happy to break down orchestration and scaling concerns before implementation starts.

@CreativeIshan

As a seasoned web developer with over ten years of comprehensive experience, I've developed a robust skill set that aligns perfectly with your project's needs. While my particular strengths lie in WordPress Development, Full-Stack Web Development, and UI/UX Design, my proficiency in technologies such as Python and my prior exposure to AI/ML libraries like TensorFlow only enhances my versatility and expertise in handling the demands of this role. I have an extensive catalog of successful projects under my belt, which acts as a testament not only to my technical acumen but also my ability to deliver results-driven solutions within the required timeframe. I'm meticulous about details, and I believe that this discipline is particularly valuable when working on complex projects such as Generative AI systems. Moreover, I'm no stranger to operating in fast-paced agile environments and have a demonstrated ability to juggle multiple responsibilities. With that being said, I know the value of clear communication and consistent collaboration, and would ensure my work complements that of your team members effectively for optimal project success. Let's connect and start building something amazing together!

@nileshp801

➡️ Multi-Agent Generative AI System with LangGraph & RAG Architecture Having meticulously evaluated your project, I am confident this aligns perfectly with my 7+ years of software engineering experience and deep expertise in Generative AI, multi-agent systems, RAG architectures, and LLM fine-tuning. I will design and build a production ready multi-agent system capable of reasoning, planning, and executing complex tasks using LangChain, LangGraph, or Crew AI. ✅ My Blueprint ✔ Multi-Agent System Design ➡️ Custom agentic workflows with specialized agents (research, planning, execution, review) ➡️ State management, tool calling, and human in the loop support ➡️ Reasoning and planning capabilities using ReAct or similar patterns ✔ RAG & LLM Integration ➡️ Vector database setup (Pinecone, Weaviate, or Chroma) ➡️ Open source LLMs (LLaMA, Mistral) or OpenAI/Gemini/Azure OpenAI ➡️ Prompt engineering, few shot learning, and optional fine tuning ✔ Backend & Cloud ➡️ Python FastAPI based agent orchestration layer ➡️ Docker containerization, serverless ready ➡️ PostgreSQL and DynamoDB for memory and state ✔ Delivery ➡️ Modular, testable agent code, API documentation, deployment guide ✅ Solution Framework ➲ Python + LangChain / LangGraph / Crew AI ➲ OpenAI / Gemini / Azure OpenAI or LLaMA / Mistral ➲ Vector DB (Pinecone / Weaviate / Chroma) ➲ FastAPI + Docker + PostgreSQL + DynamoDB Ready to start immediately. Let's build intelligent agents that reason and act. Nilesh P.