AI/ML Engineer (LLM & Agent Systems)

@BrightDock

We’ve built powerful LLM-powered systems and agent architectures for real-world applications. This project is a perfect match for us. Relevant Work: Airbus AI System: Integrated LLMs, custom data pipelines for real-time decisions. Autonomous Agents: Multi-agent workflows using LangChain and LangGraph. Skills: Tech: Python, RAG, FAISS, Pinecone, LangChain, LangGraph, OpenAI, Anthropic. Infrastructure: Docker, Kubernetes, microservices, real-time systems. Are you available TODAY for a quick call to chat about this?

@neerajdhameliya

Hello, Building autonomous agents is more than just chat. The real challenge is making them reliable, handling API failures, long tasks, and loops without breaking. I use LangGraph to build structured workflows with clear guardrails and human checkpoints to keep everything stable and predictable. For RAG, I go beyond basic vector search by using hybrid search and re-ranking to improve accuracy at scale. I focus on production-ready systems, with tools like LangSmith for monitoring and RAGAS for evaluation. With 8 years of experience, I’ve built multi-agent systems and high-accuracy RAG pipelines used in real-world applications. Feel free to check my Freelancer profile to see some of my recent work. Looking forward to discussing this further. Best, Niral

@ZohaibRoy

⭐⭐⭐⭐⭐ Build Scalable LLM-Powered AI Systems for Real-World Execution ❇️ Hi My Friend, I hope you are doing well. I reviewed your project requirements and see you are looking for an expert to build LLM-powered systems. Look no further; Zohaib is here to help you! My team has successfully completed over 50 similar projects in AI system development. I will focus on creating efficient agent architectures and pipelines to ensure your project's success. ➡️ Why Me? I can easily develop your scalable AI systems as I have 5 years of experience in Python, LLMs, and RAG pipelines. My skills include working with vector databases and API integrations. Additionally, I have a strong grip on distributed systems and multi-agent architecture, which will be beneficial for your project. ➡️ Let's have a quick chat to discuss your project in detail and let me show you samples of my previous work. I look forward to discussing this with you in our chat. ➡️ Skills & Experience: ✅ Python Development ✅ LLM Integration ✅ RAG Pipeline Design ✅ API Development ✅ Vector Databases (FAISS, Pinecone) ✅ LangChain / LangGraph ✅ Data Ingestion ✅ Monitoring Systems ✅ Performance Optimization ✅ Multi-Agent Workflows ✅ Real-Time Systems ✅ Docker & Kubernetes Waiting for your response! Best Regards, Zohaib

@technosystem

As a long-time freelancer with nearly 20 years of experience, I'm excited to dive into the complex and data-driven world of AI/ML engineering. While my skills lie mostly within graphic design, blockchain and web/mobile development, I also possess a strong understanding of Machine Learning and have worked with Python extensively, which aligns well with your project requirements. Even though I don't have direct experience in LLM-powered applications just yet, my ability to quickly pick up new tools and technologies combined with my solid grasp of APIs and microservices will enable me to make swift progress in contributing to your project. Additionally, my experience in creating distributed systems and optimizing performance can prove invaluable when it comes to designing scalable AI systems and improving latency. My extensive serves as proof that I can take concepts from ideation all the way to deployment, which is something you've explicitly mentioned in your ideal candidate description. Furthermore, my ability to think in systems rather than just models, coupled with my drive for real-world execution will align well with your project vision. Your project poses an exciting challenge that I am eager to take up and together create a cutting-edge LLM-powered system capable of real-world execution and decision-making.

@Mahihassi

With a deep understanding of AI and cloud development, I am confident that I can build the robust LLM-powered systems your project needs. My experience encompasses all the elements mentioned in your project description - from designing and optimizing RAG pipelines to building and managing multi-agent workflows. Not only have I worked with popular LLMs like OpenAI and Anthropic, but I've also used vector databases such as FAISS, Pinecone, Weaviate, Milvus extensively in my projects, giving me a solid working knowledge of retrieval and re-ranking systems. These skills combined with my expertise in scalable backend architectures will ensure that the AI system we create for you is not just high-performing but also cost-effective and latency optimized. But more than my skills, what I bring to the table is a mindset that focuses on real-world execution. Having worked extensively with startups, I've learned to quickly move from concept to production, ensuring that our work aligns with your practical business needs. Let's combine your ambitious vision with my technical expertise to build an AI system that truly transforms how decisions are made in your domain!

@Herculesz

Hi I can help architect and build production-ready LLM systems that go beyond simple text generation and can interact with tools, APIs, data pipelines, and real-world workflows. The main technical challenge is making agentic AI reliable at scale, especially around retrieval accuracy, tool-use control, latency, cost, observability, and evaluation. I have hands-on experience with Python, OpenAI/Anthropic-style LLM integrations, RAG pipelines, embeddings, vector databases, LangChain/LangGraph, LlamaIndex, APIs, and backend system design. I can design hybrid search, re-ranking, data ingestion, multi-agent workflows, async task execution, monitoring, logging, and evaluation frameworks for LLM outputs. My approach is to build modular systems with clear boundaries between retrieval, reasoning, tool execution, memory, orchestration, and safety controls. I can also support deployment workflows using Docker, CI/CD, cloud infrastructure, and scalable API services for production use. Thanks, Hercules

@irsolutions

I understand your need for an AI/ML Engineer with expertise in LLM-powered systems and autonomous agent architectures. With a decade of experience in high-complexity systems and a track record of scaling applications for over 1 million users, I am well-equipped to tackle the challenges of building scalable AI systems like the one you envision. A strategic insight for ensuring scalability and performance in this project would be to implement a robust evaluation framework for LLM outputs, ensuring efficient decision-making and real-world execution. My past success in building Telegram Mini Apps for 1 million users demonstrates my ability to handle projects of this magnitude with precision and efficiency. I encourage you to reach out to discuss how we can collaborate on bringing your AI system to life. Let's connect to delve into the details of your project's roadmap and how I can contribute to its success.

@diektech

Hi, This is Elias from Miami. I have gone through your project description and understand you’re looking to build LLM-powered systems that can take actionable steps, rather than just providing responses. This sounds like an exciting challenge! I have experience in AI development and have successfully delivered projects involving machine learning and AI model integration. I believe my background would be a great fit for your requirements. To approach this project, I would focus on defining the specific actions the LLM should take and how it will integrate with existing systems. I would also ensure efficient data handling and scalability as user demands grow. I have a few questions to get a better understanding: Q1 – What specific actions do you envision the LLM taking within the system? Q2 – Are there any existing systems or APIs that this project needs to integrate with? Q3 – What is the expected volume of data that the LLM will need to process? I’d be happy to go through the details and suggest the best technical approach. Looking forward to hearing from you.

@ludiac

Hi, I specialize in building production-grade LLM systems, including RAG pipelines and autonomous multi-agent architectures. I’ve developed systems using Python, LangChain/LangGraph, and vector databases like FAISS and pgvector, focused on real-world execution not just text generation. My experience includes designing end-to-end pipelines: data ingestion → embedding → hybrid retrieval → re-ranking → grounded generation, along with tool-use agents integrating APIs and workflows. I also optimize latency, cost, and scalability using async processing and containerized deployments. Relevant RAG projects: https://www.freelancer.com/projects/php/Sharepoint-RAG-SQL-GPT-agent/reviews https://www.freelancer.com/projects/php/SQL-RAG-GPT-Agent-with/details I can take full ownership from architecture to production and scale systems efficiently. Happy to share GitHub and discuss your requirements. Thanks.

@corpmember29

I WILL BUILD PRODUCTION-GRADE AI AGENTS THAT ACT, NOT JUST RESPOND. We bring 12+ years in backend/AI systems with hands-on delivery of LLM apps, RAG pipelines, and agent workflows running in production. Relevant Experience: RAG systems (hybrid search + re-ranking) using FAISS/Pinecone Multi-agent workflows with LangChain / LangGraph (tool use, orchestration) LLM integrations (OpenAI, Anthropic, open-source models) Data pipelines (ingestion → embedding → retrieval → response) Real-time APIs, async workers, and scalable microservices Approach Design modular architecture (LLM layer, retrieval layer, tool layer Build RAG with optimized chunking, embeddings, and ranking Develop agent systems that call APIs, trigger actions, and manage state Implement evaluation (latency, cost, NDCG, response quality) Add monitoring, logging, and feedback loops for continuous improvement Tech Stack: Python, FastAPI, LangChain/LangGraph, vector DBs (Pinecone/Weaviate), Redis, Docker, Kubernetes, AWS Why Us: Focus on real-world execution systems, not just prompts Strong system design + production mindset Fast iteration with measurable performance improvements Portfolio, GitHub, and project demos available on request. Ready to build scalable, action-driven AI systems immediately.

@tangramua

Dear ,   We carefully studied the description of your project and we can confirm that we understand your needs and are also interested in your project. Our team has the necessary resources to start your project as soon as possible and complete it in a very short time.   We are 25 years in this business and our technical specialists have strong experience in Python, Ruby on Rails, Machine Learning (ML), Hadoop, PostgreSQL, Large Language Model, AI Chatbot Development, AI Model Development, AI Model Integration, AI Development and other technologies relevant to your project.   Please, review our profile https://www.freelancer.com/u/tangramua where you can find detailed information about our company, our portfolio, and the client's recent reviews.   Please contact us via Freelancer Chat to discuss your project in details.    Best regards, Sales department Tangram Canada Inc.     

@juanjosec63

Hi, I have strong experience building production-grade LLM systems in Python, including RAG pipelines, tool-using agents, and API-driven AI workflows using OpenAI and LangChain/LangGraph. I’ve worked on systems that combine vector search, embeddings, and multi-step reasoning pipelines designed to move from prototype to real-world execution. For this project, I will design and develop a scalable AI architecture that integrates LLMs with tool execution, RAG retrieval pipelines, and multi-agent workflows. This includes setting up ingestion pipelines, vector database integration, and hybrid search with re-ranking to ensure accurate context retrieval. I will also build agent systems capable of interacting with APIs and external tools, while optimizing latency, cost, and reliability. On top of that, I will implement evaluation and monitoring layers so you can track performance, quality, and decision accuracy in production. Best regards, Juan

@kareemmaize

Hi there To build “LLM-powered systems that take actions” and “autonomous agent architectures,” the most critical part is controlling how agents make decisions when interacting with tools, APIs, and live data. I’ll approach this by structuring agent workflows with clear state transitions and tool boundaries, and designing RAG pipelines with hybrid retrieval and re-ranking to ensure reliable context before any action is triggered. This means I understand how to prevent failure loops, hallucinated actions, and inconsistent outputs in multi-agent systems. My process is simple: Map decision flows and define agent roles, memory, and tool access Build RAG pipelines with embeddings, retrieval layers, and ranking control Validate execution paths with logging, evaluation metrics, and real scenario testing I’m ready to start with system flow design and agent architecture mapping. Final timeline and budget will be defined precisely once the full scope and requirements are confirmed. If this aligns with you, let’s discuss in detail via private chat.

@noursherif030

As a versatile software engineer with a solid degree in Software Engineering and Information Systems, I have honed my skills that perfectly meet your project's requirements. I possess a deep understanding of Python and years of production experience which will be indispensable for this position. The most valuable part of my profile for your project is my past exposure with LLMs (OpenAI, Anthropic, etc.) as well as RAG systems & embeddings - an ideal blend you are searching for. And this is not just theoretical knowledge, but hands-on experience. I have actually worked with these systems extensively and achieved real-world execution, focusing on latency optimization and better performance. Moreover, I am well conversant and experienced in API integrations, distributed systems, and microservices, skills that will come into play and bring greater efficiency to your project. Not only this, but I am also familiar with Docker, Kubernetes, CI/CD to ensure a seamless development pipeline for the whole project.

@Feriver

Hello, I will design and develop a production-ready AI/LLM system focused on real-world execution, combining agent-based workflows, RAG pipelines, and tool-using architectures. The system will be built with a modular design so it can scale from prototype to production without rework. I will implement LLM integration (OpenAI/Anthropic/open-source models), structured RAG pipelines with embeddings, retrieval, and reranking, and agent orchestration using LangGraph or equivalent frameworks. The architecture will support tool use via APIs, external services, and data pipelines for autonomous task execution. On the infrastructure side, I will ensure performance optimization, logging, evaluation frameworks, and monitoring for cost, latency, and accuracy. The system will be designed with clean APIs, async processing where needed, and production-grade deployment practices using Docker and scalable backend patterns. Thanks, Asif

@mugencodes

Hello, I understand the importance of building LLM-powered systems that not only generate outputs but also take actions. Your project's focus on autonomous agent architectures interacting with various tools, APIs, and data pipelines aligns with my expertise in Python, AI development, and machine learning. I have hands-on experience with LLMs from OpenAI and Anthropic, as well as designing and optimizing RAG pipelines. My skills in building scalable AI systems, managing multi-agent workflows, and implementing evaluation frameworks for LLM outputs make me a suitable candidate for this project. Additionally, my familiarity with vector databases like FAISS and LangChain/LangGraph further strengthens my capabilities in this area. I am confident that my background in backend development, infrastructure management, and AI layers will allow me to architect and develop the sophisticated AI systems you require. I look forward to the opportunity to contribute to your project. Best regards, Jayabrata Bhaduri

@markupdudes

Hi, I’m excited about your project focusing on building LLM-powered autonomous agent systems and scalable AI architectures. With strong Python experience and hands-on work with OpenAI and Anthropic LLMs, I’ve developed RAG pipelines integrating vector databases like FAISS and Pinecone. I’m proficient in LangChain and LangGraph for crafting multi-agent workflows that interact efficiently with APIs and external tools. My approach centers on real-world deployment and performance optimization, ensuring latency and cost improvements without sacrificing functionality. I can take your project from concept through production with a solid background in distributed systems, microservices, and AI evaluation frameworks. I’m comfortable working in fast-paced startup settings and tackling the full stack of this complex AI ecosystem. I’d propose starting with a detailed design session and setup of RAG pipeline components followed by agent system development within a timeline of about 15 days, allowing iterative testing and tuning. Could you share more about the current infrastructure and any specific APIs or data tools you want integrated? Best regards,

@mughiraaa

Hello, I will use python as the core language with fastapi to expose api endpoints for agent workflows and system orchestration, while integrating llm providers such as openai or anthropic for reasoning tasks. rag pipelines will be designed using langchain or langgraph with document ingestion pipelines that clean, chunk and embed data into a vector database such as pinecone or faiss, combined with hybrid search using keyword and embedding retrieval with reranking for accuracy. agent workflows will be structured as modular chains that interact with external apis and internal tools through defined action handlers, allowing decision making and execution in real time. async processing using python asyncio will manage parallel tasks and reduce latency, while logging and monitoring will be handled through structured logs and metrics tracking. evaluation will include automated scoring of responses and retrieval quality using standard metrics and feedback loops. Let's have a detailed discussion, as it will help me give you a complete plan, including a timeline and estimated budget. I will share my portfolio in chat I look forward to hear from you. Thanks Best Regards, Mughira

@chiragardeshna

Hi there, Strong alignment with this project comes from experience delivering LLM-powered systems where scalability, tool integration, and real-world execution are essential. Clear understanding of the requirement to build RAG pipelines, multi-agent systems, and API-driven tool workflows with strong monitoring, evaluation, and performance optimization. Hands-on expertise with Python, LangChain/LangGraph, vector databases, and OpenAI/Anthropic models ensures robust, production-ready AI systems. Risk is minimized through modular architecture, evaluation frameworks, and cost/latency optimization strategies. Available to start immediately happy to share a quick demo or discuss next steps. Recent work: https://www.freelancer.com/u/chiragardeshna Regards Chirag