AI Engineer for RAG, LLM

@AwaisChaudhry

As a technology solutions company that has been providing end-to-end digital solutions for several years, ZAWN Tech is your ideal partner in this project. Moreover, I bring a wealth of experience in AI Development, AWS Lambda, and Large Language Models (LLMs) - which are essential components for your project. I’m well versed in Python,the primary language required and instrumental in search infrastructure maintenance and LLM integrations that you need. My previous projects have exposed me to different cloud-native Python development platforms. Hence, I have the capacity to handle OpenSearch and AWS Bedrock comfortably as well as optimizing retrieval latency and LLM response accuracy. My deep proficiency in Python goes beyond just coding; I have an ingrained understanding of vector databases and retrieval-augmented generation (RAG). This skillset fits perfectly with the role in managing and configuring OpenSearch clusters as well as building APIs for LLM integration. Additionally, having transitioned systems from traditional keyword search to hybrid or semantic search, it's evident that I encompass the skills needed for retooling the search system to incorporate Large Language Models. My proven ability to produce fast, secure, and scalable applications aligns well with your needs. Above all, my dedication is always geared towards delivering high-quality work on-time. JoAppendix Sincerely,Muhammad Awais

@MashoodurRehman1

I am a seasoned AI Engineer with a strong background in Python and cloud-native development, specifically within AWS environments. My extensive experience with OpenSearch, LLMs, and vector databases aligns well with your needs. I have managed and optimized OpenSearch clusters, focusing on k-NN and vector search capabilities, and proficiently integrated LLMs including those from OpenAI and Anthropic. My work in retrieval-augmented generation and prompt engineering, combined with designing and deploying AWS Lambda functions, has equipped me with the skills to develop robust search infrastructures. I have transitioned systems from keyword to hybrid search, and my familiarity with LangChain and LlamaIndex strengthens my ability to enhance AI feature development and API design to create seamless, efficient solutions. I am interested in discussing how my skills can contribute to maintaining and evolving your search system. Could we set up a time to discuss your specific challenges and goals? I look forward to the opportunity to contribute to your project.

@neerajdhameliya

Hello, My proudest achievements: 1. Graphology: An AI tool that analyzes handwriting using OpenCV, feature extraction, and ML models (including trained YOLO classification and detection) to find patterns in stroke, slant, spacing, and more for personality and forensics research. 2. Terramatic: A real-time road sign detection system with YOLO (Ultralytics) and OpenCV. It also classifies road types (national highway, city, village) using segmentation, detection models, and Google Maps coordinates to check road quality like curve and slope. I have deep knowledge in: => Vector databases and semantic/hybrid search (including transitions from keyword to vector-based systems) => Building RAG pipelines with prompt engineering => Python backend development => Integrating LLMs via APIs (OpenAI, Anthropic, AWS Bedrock) => AWS Lambda for serverless functions => OpenSearch configuration, vector search (k-NN), indexing, and optimization I can help you maintain and improve your OpenSearch + LLM search system: optimize vector retrieval for lower latency, refine RAG pipelines for better accuracy, tune prompts, build Lambda functions to connect everything, and support future AI features. I am excited to work independently and communicate clearly in a fast-paced setup. Looking forward to your reply and helping your team succeed. Best regards, Niral

@ZohaibRoy

⭐⭐⭐⭐⭐ Senior Engineer for Advanced Search Infrastructure and AI Integration ❇️ Hi My Friend, I hope you're doing well. I reviewed your project and see you are looking for a Senior Engineer to enhance your search infrastructure. Look no further; Zohaib is here to help you! My team has completed 50+ similar projects focused on search systems and AI integration. I will efficiently manage OpenSearch clusters, develop API integrations with LLMs, and optimize performance to meet your needs. ➡️ Why Me? I can easily handle your search infrastructure and AI integration project as I have over 5 years of experience in Python development, OpenSearch management, and AI feature creation. My strong expertise in vector databases, RAG, and AWS services ensures a comprehensive approach to your project. ➡️ Let's have a quick chat to discuss your project in detail. I can show you samples of my previous work and how I can add value to your project. Looking forward to discussing this with you! ➡️ Skills & Experience: ✅ Python Development ✅ OpenSearch Management ✅ LLM Integration ✅ API Development ✅ AWS Lambda ✅ Vector Databases ✅ Retrieval-Augmented Generation (RAG) ✅ Performance Tuning ✅ Prompt Engineering ✅ Serverless Functions ✅ Cloud Solutions ✅ Semantic Search Waiting for your response! Best Regards, Zohaib

@irsolutions

With over 10 years of experience in AI/ML development, I understand the importance of maintaining and evolving a sophisticated search infrastructure like the one you described for RAG, LLM integration with AWS Lambda. My expertise in Python, OpenSearch, and AWS align perfectly with your key requirements. I have successfully implemented AI features and optimized performance in various projects, including fintech and healthcare solutions. Working on search infrastructure for large-scale applications is where I excel, and I am excited about the opportunity to contribute to your project. If you are looking for a highly skilled Senior Engineer to drive your search system forward, I am ready to jump in and help. Let's discuss how I can support your team and contribute to the success of your project.

@vladang

Hi, I’d like to start by highlighting a recent achievement I’m particularly proud of: I led the migration of a legacy keyword search system to a semantic, vector-search architecture powered by OpenSearch and LLMs, integrating a retrieval-augmented generation (RAG) pipeline that reduced average query latency by 40% while improving answer relevance significantly. I’m an experienced Python engineer with deep expertise in OpenSearch, including k-NN and vector search, and have built serverless architectures with AWS Lambda to orchestrate AI and search components. I’ve designed and maintained RAG pipelines, worked on prompt engineering and fine-tuning models, and integrated LLMs via APIs including OpenAI and AWS Bedrock. I’m comfortable with RESTful API design, performance tuning, and hybrid search systems, and have used frameworks like LangChain and LlamaIndex to create scalable retrieval solutions. I thrive in fast-paced, independent environments and would be excited to help maintain and evolve your search infrastructure while implementing advanced AI-driven features. Best regards,

@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 Java, Python, Machine Learning (ML), Amazon Web Services, RESTful, AWS Lambda, Large Language Model, Large Language Models (LLMs), AI Development, Retrieval-Augmented Generation (RAG) 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.     

@Herculesz

Hi My proudest achievement is leading a production migration from keyword-only search to hybrid vector search, cutting retrieval latency by 45% while improving answer accuracy in a RAG system used by thousands daily. I specialize in Python, OpenSearch (k-NN/vector search), AWS Lambda, AWS Bedrock, and LLM integrations with OpenAI/Anthropic. A major technical risk in systems like yours is high latency and low relevance when vector indexes, filters, and LLM prompts are not tuned together. I solve this by optimizing index mappings, shard strategy, k-NN parameters, and hybrid scoring so keyword and semantic signals reinforce each other. RAG pipelines will use structured chunking, embedding versioning, and retrieval evaluation loops to keep answers stable and explainable. LLM calls will be cost- and latency-controlled with caching, prompt templates, schema validation, and fallback logic across providers. AWS Lambda will orchestrate search and AI flows using event-driven design, retries, and observability hooks for debugging and tuning. The result is a fast, accurate, and maintainable search + AI stack that scales without losing quality. Thanks, Hercules

@hireageek

Hi, I'm excited about the opportunity to contribute to your search infrastructure, especially with my proudest achievements in developing highly scalable systems that integrate AI and cloud technologies. I have successfully optimized search systems using OpenSearch while implementing advanced features with Large Language Models (LLMs). My experience aligns perfectly with your requirements, particularly around retrieval-augmented generation (RAG) and cloud-native Python development. Having managed OpenSearch clusters, I have a deep understanding of configuring and fine-tuning vector search capabilities. I am also adept at developing efficient integrations with APIs and deploying serverless functions using AWS Lambda to create seamless workflows between your search and AI components. I am dedicated to enhancing performance, ensuring minimal latency, and maximizing response accuracy in line with your project goals. I would love to discuss how I can help your team. Please message me at your earliest convenience. What challenges are you currently facing with your search infrastructure that you would like me to address?

@Muhammadzeesha59

As a seasoned Senior Full Stack Developer with over 6 years of experience, my bag of skills is precisely suited to handle your AI Engineering project. My proficiency in Python, Java, and C++, coupled with a deep understanding of Machine Learning and RESTful APIs make me the ideal candidate for a project that requires managing complex infrastructures like OpenSearch clusters and vector databases. In addition to my long-term experience with LLM concepts like RAG, Prompt Engineering, and Fine-tuning, I bring comprehensive knowledge of AWS Lambda and AWS Bedrock to the table. These skills will be crucial for integrating your search system with Large Language Models (LLMs) via APIs like OpenAI or Anthropic. I have also worked extensively on maximizing serverless functions for seamless coordination between search and AI components. My focus has always been on delivering top-quality solutions within budget while providing the best client experience possible. I'm also adept at working independently in fast-paced environments - a key quality you're seeking in a contractor. Overall, my broad range of skills and my commitment to accuracy, efficiency, and constant improvement make me confident that together we can elevate your project to new heights.

@devendrathakur12

Hello, I built & customized large scale search systems where OpenSearch, vector search, and LLMs power real products used daily. My proudest work was turning a slow keyword search into a fast semantic search using OpenSearch k-NN and RAG, cutting response time by more than half. Looking forward to discuss your project in detail. I’m certified in Python and AWS development and have hands-on experience with OpenSearch, AWS Lambda, and Bedrock. I wire search and LLMs cleanly so the system stays fast, simple to debug, and cheap to run. I also focus on clear logs and safe rollouts, which saves teams pain later. A few quick questions: How big is the current index and vector size? Are you using hybrid search already or planning to add it? Which LLMs are live today? What latency target matters most to you? Is cost or accuracy the top priority right now? Best regards, Dev S.

@shanec35

Hi there, My proudest achievement is leading the migration of a production search platform from keyword-only OpenSearch to a hybrid semantic search using vector embeddings and RAG, cutting average query latency by 35% while significantly improving answer relevance for end users. I’m a senior Python engineer with deep hands-on experience managing and optimizing OpenSearch clusters, including k-NN vector indexing, hybrid retrieval strategies, and performance tuning at scale. I’ve built RAG pipelines that combine OpenSearch with LLMs (OpenAI and AWS Bedrock), using careful prompt engineering and retrieval strategies to improve accuracy and reduce token waste. On the backend side, I regularly design serverless architectures using AWS Lambda to orchestrate search, embedding generation, and LLM calls. I’m comfortable building clean REST APIs, optimizing cold starts, and monitoring latency across the full retrieval and generation pipeline. I’ve also worked with LangChain and LlamaIndex where they add value, without over-engineering. I can start immediately and work independently in a fast-paced environment while communicating clearly and proactively. Best regards, Elenilson

@maximg10

⭐Hi, I’m ready to assist you right away!⭐ I believe I’d be a great fit for your project since I have spearheaded the development of sophisticated search systems integrating OpenSearch with Large Language Models (LLMs) while optimizing retrieval latency and enhancing search accuracy with AI features. My extensive experience in Python, vector databases, and cloud-native development aligns perfectly with the requirements of your project. Specifically, my expertise in vector search, RAG pipelines, and AI integration make me confident in delivering exceptional results for RAG, LLM project. If you have any questions, would like to discuss the project in more detail, or would like to know how I can help, we can schedule a meeting. Thank you. Maxim

@Rekhathakur

With over a decade of experience in AI Engineering and Machine Learning, I've amassed expertise that suits your needs exceptionally well. From pioneering Retrivial-Augmented Generation systems using FAISS and Pinecone to integrating LLMs via APIs, I am well-versed in building and maintaining complex search infrastructures precisely like you need. Not only do I have a strong familiarity with OpenSearch, but my skills extend into optimizing search systems, minimizing retrieval latency and maximizing LLM response accuracy. Facilitating synergy between backend engineering and cloud native development has been my forte. I’ve worked extensively with AWS Lambda in developing serverless functions that seamlessly bridge the gap between search and AI components. My solid understanding of cloud technologies further allows me to leverage AWS Bedrock to the fullest. Moreover, my clients often appreciate my ability to constantly exceed expectations by delivering business outcomes, not just features. The projects I've executed are not limited to code; they effectively solve business problems - saving time, reducing costs. In hiring me you get a well-rounded, efficient freelancer capable of creating specialized AI solutions while keeping the larger business goals in mind!! Thank you!!!

@denisSolution

Hello client, I'm Denis Redzepovic, an experienced developer with expertise in Large Language Models (LLMs), Python, Java, RESTful, Retrieval-Augmented Generation (RAG), Large Language Model, AWS Lambda, Machine Learning (ML), Amazon Web Services and AI Development. I have worked extensively on diverse Python projects, ranging from backend development and automation to data processing and API integrations. My deep understanding of Python’s libraries and frameworks allows me to build efficient, scalable, and maintainable solutions. I pay close attention to code quality and performance to ensure your project runs flawlessly. With my solid experience, I’m confident I can deliver results that exceed your expectations. I focus on writing clean, maintainable, and scalable code because I know the difference between 99% and 100%. If you hire me, I’ll do my best until you’re completely satisfied with the result. Let’s discuss your project details so I can tailor the perfect Python solution for you. Thanks, Denis

@quan9824

As a highly experienced professional with a 100% job completion rate and a strong background in AI and software development, I am well-equipped to handle every aspect of this project. With robust skills in machine learning, deep learning, and text generation, I am adept at the sophisticated tasks required for implementing and refining RAG pipelines. Additionally, my knowledge of AWS Lambda and Bedrock complements your requirements perfectly and can be instrumental in the smooth integration of LLMs. What sets me apart is my ability to transition systems innovatively. I have unique experience moving projects from traditional keyword search to hybrid or semantic search - a proficiency that aligns directly with your "preferred qualifications". My dedication to communication and understanding client's needs has allowed me to build exceptional working relationships, characterizing my work as dynamic, dependable, and always in line with your schedule. As you consider candidates for this critical role, I encourage you to review my track record of delivering high-quality work on time; I believe it speaks volumes about the dedication I bring to every project. My diverse skillset coupled with my passion for the task will ensure seamless management, optimization, and evolution of your search infrastructure powered by OpenSearch, LLM's, and AWS Lambda. Thank you for considering me for this exciting opportunity; I look forward to discussing how we can take this project forward together!

@Julian29

Hello My proudest achievement was leading the design and operation of a production-grade RAG platform serving millions of monthly queries, migrating a legacy keyword search system to a hybrid semantic search using OpenSearch, and delivering low-latency LLM-powered APIs on AWS Lambda with significantly improved relevance and performance. I am a Senior AI Engineer with 10+ years of experience in Python backend engineering and advanced AI systems, with deep hands-on expertise in vector databases, OpenSearch (k-NN and vector indexing), and retrieval-augmented generation. I’ve built and maintained RAG pipelines integrating OpenSearch with OpenAI, Anthropic, and AWS Bedrock, focusing on accuracy, latency, and cost efficiency. My work includes prompt engineering, hybrid retrieval strategies, evaluation loops, and fine-tuning support, all deployed via cloud-native, serverless architectures using AWS Lambda. I also have strong experience designing and consuming RESTful APIs and optimizing end-to-end search performance. I’ve successfully transitioned systems from traditional keyword search to semantic and hybrid approaches, and I’m familiar with LangChain and LlamaIndex where appropriate. I work independently, communicate clearly, and thrive in fast-paced environments where production reliability matters most. Thanks.

@abhisaini0188

Hello, Thank you so much for posting this opportunity. It sounds like a great fit, and I’d love to be part of it! I’ve worked on similar projects before, and I’m confident I can bring real value to your team. I’m passionate about what I do and always aim to deliver work that’s not only high-quality but also makes things easier and smoother for my clients. Feel free to take a quick look at my profile to see some of the work I’ve done in the past. If it feels like a good match, I’d be happy to chat further about your project and how I can help bring it to life. I’m available to get started right away and will give this project my full attention from day one. Let’s connect and see how we can make this a success together! Looking forward to hearing from you soon. With Regards! Abhishek Saini

@dvcontact

Hello, Are you ready to leverage cutting-edge AI and enhance your search infrastructure with a demo that highlights its potential? I specialize in integrating OpenSearch with LLMs, utilizing a deep understanding of RAG and cloud-native Python development to optimize search capabilities. Let's discuss how I can bring transformative solutions to your project. Best, Smith