AWS AI Engineer

@Fazeennazar

Hi, I’m very interested in the AWS AI Engineer role and have hands-on experience building agentic AI systems on AWS. I’ve implemented LLM-powered workflows using AWS Bedrock with frameworks like LangChain and AutoGen for structured reasoning and multi-agent communication. I’m experienced in designing event-driven architectures with Lambda, Step Functions, and EventBridge for scalable AI pipelines. My background includes prompt engineering, RAG optimization, and integrating external systems through secure REST APIs. I’ve worked with AWS AI services such as SageMaker, Textract, and Comprehend, and understand how to build PHI/PII-safe ingestion pipelines. In previous projects, I focused on monitoring accuracy, latency, and compliance while iterating quickly on model performance. I’m comfortable coding in Python and TypeScript and collaborating closely with data engineering teams. I’d welcome the opportunity to discuss how I can help deliver reliable, compliant, and production-ready AI workflows for your healthcare solutions. Thanks.

@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

@divumanocha

With over a decade of experience, I am an accomplished AI Engineer well-versed in the LLM/agentic AI development and optimisation that your project demands. My background in Computer Science combined with an extensive track record in Machine Learning make me a valuable asset to any team implementing AI solutions. I also have hands-on experience with many AWS AI services such as Bedrock, SageMaker, Textract, Comprehend Medical - crucial for the successful execution of your project. Additionally, my familiarity with event-driven architectures and API integrations will ensure smooth integration of the AI agents leading to secure and efficient workflows. As a strong communicator and collaborator, I can seamlessly collaborate with data engineers on PHI/PII-safe ingestion pipelines which are vital in healthcare projects like yours. Drawing from my exposure to SaaS-based solutions and Life Sciences domains in previous projects, I can deliver your project while strictly adhering to regulatory compliances. My vast experience in building robust systems coupled with my dedication to quality and client satisfaction makes me stand out for your project requirement. Let's discuss further how we can create a transformative solution together. Thanks....

@corpmember29

I HAVE BUILT SIMILAR AWS AI WORKFLOWS AND LLM-POWERED AGENTS AND CAN SHOW YOU. With 10+ years of experience in AI/ML engineering, I specialize in AWS Bedrock, LangChain, AutoGen, and event-driven architectures. I can implement agentic AI pipelines for clinical source verification, discrepancy detection, and intelligent query generation while ensuring regulatory compliance in healthcare/Life Sciences environments. Key expertise: LLM Agents: Prompt optimization, RAG, multi-agent coordination AWS Services: Lambda, Step Functions, EventBridge, SageMaker, Textract, Comprehend Medical Programming: Python and TypeScript, secure API integration Data Handling: PHI/PII-safe ingestion pipelines, event-driven workflows, accuracy & latency optimization I WILL PROVIDE 2 YEAR FREE ONGOING SUPPORT AND COMPLETE SOURCE CODE FOR AI WORKFLOWS. Using agile methodology with daily commits and incremental testing, I can deliver scalable, production-ready AI pipelines rapidly. I eagerly await your positive response to implement AWS-powered LLM agents and intelligent clinical AI workflows efficiently.

@quan9824

As an experienced Full-Stack Developer with a strong command over AI systems, including Machine Learning and Deep learning, I strongly believe I’m the perfect fit for this AWS AI Engineer role. Having worked with Machine Learning algorithms for tasks such as Image Processing, Text Data Classification and Processing, Time Series Forecasting, among many others, I bring to the table a deep understanding of optimizing prompt engineering and generation processes. Moreover, I am well-versed in software essential to this role; extensively using Python - a key requirement for this project - in recent projects for numerous ML functions. The experience of working extensively with healthcare/Life Sciences AI solutions also puts me a step ahead since regulatory compliance is a distinct feature of the field that I am already accustomed to. Pitching myself has never been my strong suit (but rest assured coding is). So instead of trying to hard-sell myself any further, let me assure you: hire Doan and you won't be disappointed. My 100% Job Completion Rate stems from my undivided attention towards clients and your satisfaction remains top priority with me. Let's build some exceptional AI workflows together!

@abhisaini0188

Hello, I am really excited about the opportunity to collaborate with you on this project! It aligns perfectly with my skill set and experience, and I’m confident I can contribute meaningfully to your vision. I genuinely enjoy working on projects like this, and I believe we can create something both functional and visually engaging. Please feel free to check out my profile to learn more about my past work and client feedback. I’d love to connect and discuss the project details further your goals, expectations, and any specific features or ideas you have in mind. The more I understand your vision, the better I can bring it to life. I am ready to get started right away and will put my full energy and focus into delivering quality results on time. My goal is not just to complete the project, but to exceed your expectations and build a long-term working relationship. Looking forward to hearing from you soon! With regards! Abhi

@Feriver

Hello, I can develop and deploy AWS-based agentic AI workflows for clinical source verification, discrepancy detection, and intelligent query generation. Using AWS Bedrock, LangChain, AutoGen, and retrieval-augmented generation (RAG), I will implement multi-agent LLM solutions with secure API integrations and event-driven pipelines. Key deliverables include: • LLM-powered AI agents integrated with clinical data pipelines via AWS Lambda, Step Functions, and EventBridge • Optimized prompt engineering, RAG, and inter-agent communication for high accuracy and low latency • PHI/PII-safe data ingestion in collaboration with data engineers, maintaining regulatory compliance • Testing, monitoring, and fine-tuning AI workflows for performance, reliability, and healthcare standards I have 3–6 years of experience in LLM and agentic AI development, Python/TypeScript programming, and healthcare-focused AI solutions on AWS, ensuring compliant, production-ready deployments. Questions: Are there existing data pipelines or repositories we need to integrate with, or should new ingestion workflows be built? Which LLM models or compliance frameworks (HIPAA, GDPR) are mandatory for this workflow?

@Julian29

Hello, >>>> Multi languages (English and Arabic)Left-To-Right (LTR) and Right-To-Left (RTL) <<<< I have 15+ years of proven experience in AI/ML engineering and confidently understand your requirement. The goal is to deliver scalable, compliant, agentic AI workflows on AWS that enhance clinical verification and intelligent query processes while maintaining PHI/PII safety. -->> Develop LLM-powered agents with AWS Bedrock and frameworks like LangChain or AutoGen -->> Build event-driven pipelines using AWS Lambda, Step Functions, and EventBridge -->> Optimize prompt engineering, RAG workflows, and multi-agent communication -->> Integrate AI agents with external systems via secure APIs -->> Monitor, test, and fine-tune workflows for accuracy, latency, and compliance I follow a clean architecture approach with secure, modular code, efficient integration, and an agile workflow. I would approach your project by mapping the AI pipelines first, validating data safety, and then iterating rapidly on the agent workflows. I’m ready to successfully implement this project from start-to-finish. Let’s create AI solutions that are not only technically robust but also compliant and impactful in healthcare operations. Thanks & regards, Julian

@Rekhathakur

With over a decade of experience building custom technology solutions, my team at WellSpring Infotech has the precise skill set you need for your AWS AI Engineer project. Our proficiency with AWS AI services, including Bedrock, Textract, Comprehend Medical, and SageMaker, ensures we can seamlessly integrate LLM-powered agents into your existing system while leveraging AWS to its full potential. Additionally, our in-depth knowledge of Python and TypeScript proves relevant as we navigate LangChain and AutoGen frameworks. Having implemented B2B and B2C software products within the Healthcare industry earlier, we possess an inherent understanding of the vital role compliance plays in AI solutions. Furthermore, our robust approach to cybersecurity and data management caters to securing PHI/PII-safe ingestion pipelines - a key competency for your project. As an entrepreneurial-focused agency, our goal aligns perfectly with yours - to accelerate growth and innovation, improve operational efficiency and customer satisfaction. Count on us to deliver exceptional work that not only meets but exceeds your expectations. Let’s create innovative AI workflows that optimize prompt engineering, generate intelligent queries and effectively communicate across channels for your organization. Together, we'll bring positive change in clinical source verification. Thanks....

@VianRey1

When building AI-powered clinical verification, the real headache is getting agentic workflows to run smoothly and stay compliant while juggling LLMs, event-driven pipelines, and sensitive healthcare data. The frustration often comes from clunky integrations, slow response times, or compliance risks that can quickly derail progress. With the right approach, you can have accurate, event-driven AI agents on AWS that reliably spot discrepancies, automate queries, and keep patient data safe. First, I’ll set up agentic AI workflows using AWS Bedrock and open-source frameworks. Then, I’ll connect these agents to your event-driven architecture and secure APIs. Finally, I’ll monitor and fine-tune the pipelines so they stay accurate and compliant in real-world use. What’s your top priority right now: accuracy, speed, or compliance for your clinical source verification?

@bindmission

Hello, I have 10 years of experience in AI and AWS cloud technologies. I specialize in developing agentic AI solutions for healthcare, ensuring compliance and precision. My expertise includes implementing AI workflows, leveraging AWS services, and integrating LLM-powered agents. I am proficient in Python, TypeScript, and have deep experience with LangChain and AutoGen frameworks. I am confident in delivering innovative, secure, and efficient AI workflows. Regards, VishnuLal NB.*

@RusianD

Hello, In recent projects, I implemented multi-agent AI systems combining AWS Lambda, Step Functions, and vector retrieval pipelines, improving response accuracy while reducing latency and execution cost without changing core model behavior. For your clinical source verification and discrepancy detection workflows, I will focus first on building a reliable agent architecture that ensures accuracy, traceability, and compliance. I will implement Bedrock-powered agents integrated with LangChain or AutoGen, enabling structured reasoning, intelligent query generation, and controlled multi-agent communication. My approach includes: - Designing secure RAG pipelines with PHI/PII-safe ingestion and controlled document retrieval. - Building event-driven AI workflows using Lambda, EventBridge, and Step Functions for scalable processing. - Integrating external clinical or enterprise systems through secure API layers. - Optimizing prompts, evaluation loops, and agent orchestration to reduce hallucinations and improve verification accuracy. - Implementing monitoring, logging, and testing pipelines to validate performance, latency, and compliance requirements. I also have experience integrating document intelligence services such as Textract and medical NLP pipelines aligned with regulated environments where auditability and data protection are critical. Best regards, Ruslan D

@jennifersmit842

Hi there, I hope you are doing well. Requirement: Python, Django Python Backend Developer with over 11 years of experience specializing in scalable web apps, REST APIs, IoT integrations, and machine learning-enabled systems. Strong background in team leadership, AWS cloud architecture, and Django-based microservices. Technical Skills Languages & Frameworks: Python, Django, Flask, Falcon, Django REST Framework Web Technologies: HTML, CSS, Angular, jQuery, AJAX Cloud & DevOps: AWS EC2, S3, Lambda, ECS, SNS, Docker, Kubernetes Databases: PostgreSQL, MySQL, MongoDB Version Control: Git ML/AI Tools: ML integration for analytics and prediction Key Projects: Winalytics – CRM-like system with Gmail plugin ITK – RSS + ML-based data aggregation Reppr – Digital marketing campaign platform Coro Road App – Online tutor-student collaboration tool Unicar – Car sales & purchase listing app Textking – Custom promotional SMS platform Roster Staff – Staff scheduling system. Happy to discuss further. Best Regards, Gayatri

@HiraMahmood4072

Hello I hope you're doing well. I understand you're looking for AWS AI Engineer I am the ideal candidate for your project. I have read the provided job description and I understand what you are looking for. I have over 10+ years of experience Python, Machine Learning (ML), Git, AWS Lambda, API Integration, Prompt Engineering, LangChain, AI Development, AI Agents, LLM Integration .Please feel free to further discuss the requirements and timeline for the project. I'd be happy to assist you. I am ready to start right now. ✅ No Upfront Payment ✅ Release Milestone After Completion ✅ 100% Project Completion Rate You can visit my Profile https://www.freelancer.com/u/HiraMahmood4072 Thank you

@Ussama91

I will implement agentic AI workflows, build LLM-powered agents using AWS Bedrock and open-source frameworks, and develop event-driven pipelines with AWS Lambda, Step Functions, and EventBridge, ensuring regulatory compliance and optimizing prompt engineering, retrieval-augmented generation, and multi-agent communication, with strong coding skills in Python and experience with AWS AI services. Waiting for your response in chat! Best Regards.

@SkillCrafts

I’ve spent years building production AI applications on AWS, most recently deploying a RAG-based processor that reduced query latency by 40% using Bedrock and Kendra. Your project aligns with my background in architecting scalable machine learning pipelines that thrive in high-traffic environments. I understand the nuances of balancing model performance with inference costs, ensuring you get the most ROI out of your infrastructure while maintaining sub-second responsiveness for your users. I focus on delivering production-ready code rather than just experimental models, ensuring that every deployment is stable, secure, and fully integrated with your existing cloud stack. I will leverage AWS SageMaker for end-to-end model management, from labeling to automated tuning and multi-model endpoints. I build modular architectures using AWS Lambda for serverless orchestration and EventBridge for event-driven processing, ensuring the system remains cost-effective. For LLM features, I’ll implement Amazon Bedrock integrated with LangChain for retrieval-augmented generation (RAG) workflows, while utilizing AWS Glue and S3 for the data foundation. I also prioritize security via fine-grained IAM controls and CloudWatch dashboards to track real-time model drift. This holistic approach ensures that your AI solution is not only intelligent but also scalable and observable. To ensure the architecture aligns with your scale, are you prioritizing real-time inference or batch processing? Do you have a preferred foundation model in Bedrock, or should we conduct a benchmark comparison first? I am happy to hop on a quick chat to discuss how we can streamline your deployment timeline or walk you through a demo of my previous AWS AI integrations. I look forward to hearing your thoughts and aligning on the next steps for this project to ensure we hit your technical milestones. I am available to start immediately and can adjust my schedule to fit your team's specific timezone or communication needs.

@kumarashish99

With a proven track record in AWS development and LLM-driven AI engineering, choose me - Ashish - to take your project to the next level. In my 5+ years of experience, I have honed my abilities to skillfully integrate advanced AI/ML solutions on AWS using tools like Bedrock, SageMaker, Textract, and Comprehend Medical – experiences that directly align with your specific needs. Moreover, my solutions are always built with lintegrity,'mA: applying all necessary health and patient data regulation compliances. Finally, efficient solution deployment is your priority and that's where I excel. My DevOps expertise will ensure streamlined CI/CD pipelines with robust monitoring tools like Prometheus and Grafana for real-time accuracy evaluations. Beyond that, I'm a proactive problem-solver who can optimize AI workflows for not just accuracy but also low latency. If you hire me, you’ll be employing someone dedicated, experienced, and passionate about turning your unique vision into a practical application that enables effective agentic AI workflows in clinical environmentsoften working

@rahulb058

Hi, I’ve carefully reviewed your requirement for an AWS AI Engineer to build agentic AI workflows for clinical source verification and discrepancy detection using AWS Bedrock, especially the need for event-driven pipelines (Lambda, Step Functions, EventBridge) combined with RAG and multi-agent orchestration in a PHI-safe environment. This aligns strongly with my experience in production-grade LLM systems on AWS. Your use case isn’t just LLM integration — it requires accurate, auditable, healthcare-compliant AI agents that can reason over structured + unstructured clinical data while maintaining regulatory safeguards. That’s exactly how I would architect it.

@Eliteinno

Hi, our devs looked at your project and noticed a potential bottleneck in the architecture related to scaling efficiently. Our backend lead has extensive experience optimizing similar systems, ensuring performance remains top-notch as user demand grows. By focusing on robust architecture, we can help you scale seamlessly. We recently completed a large-scale e-commerce platform that faced similar scaling challenges, using a tech stack of Node.js and React to boost performance and user engagement significantly. The end result was a 40% increase in load handling capacity without compromising speed. I'll be your direct technical point of contact, and we'll set up a staging environment to keep you in the loop throughout the process, ensuring transparency and collaboration. How do you envision the app’s functionality evolving in the next few years? Let's explore how we can bring your vision to life.