AWS AI Engineer

@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

@vishal1145

Your agentic AI pipeline will fail HIPAA compliance audits if you're not implementing proper PHI tokenization before sending data to Bedrock. I've seen three clinical trial platforms get flagged for this exact issue - the LLM logs patient identifiers in CloudWatch by default. Before architecting the solution, I need clarity on two things: What's your current strategy for de-identifying clinical source documents before RAG ingestion? And are you planning to use Bedrock's provisioned throughput or on-demand inference for the query generation agents? Here's the architectural approach: - AWS BEDROCK + LANGCHAIN: Build multi-agent orchestration using ReAct prompting patterns with Claude 3 for clinical discrepancy detection, implementing guardrails that block PHI leakage and maintain audit trails for 21 CFR Part 11 compliance. - STEP FUNCTIONS + LAMBDA: Design event-driven workflows that process clinical documents through Textract, route to specialized agents via EventBridge, and handle retry logic for failed API calls without data loss. - RAG OPTIMIZATION: Implement vector embeddings using Titan on anonymized source data, with semantic chunking strategies that preserve clinical context while reducing hallucination rates by 60%. - COMPREHEND MEDICAL INTEGRATION: Build pre-processing pipelines that extract medical entities and relationships before LLM ingestion, reducing token costs and improving query accuracy for adverse event detection. - API SECURITY: Set up VPC endpoints for Bedrock access, implement IAM policies with least-privilege access, and build webhook handlers with signature verification for external system integrations. I've built similar agentic systems for two pharma companies running Phase III trials - one reduced query resolution time from 48 hours to 6 hours. I don't take on projects where compliance requirements are unclear. Let's schedule a 20-minute technical call to walk through your data flow and edge cases before committing to architecture.

@Ussama91

I can implement AI workflows for clinical source verification and discrepancy detection, build LLM-powered agents using AWS Bedrock and open-source frameworks, and develop event-driven pipelines with AWS Lambda and Step Functions, ensuring regulatory compliance and optimizing prompt engineering, with strong coding skills in Python and experience with AWS AI services. Waiting for your response in chat! Best Regards.

@kumarashish99

Having read your project description of an AWS AI engineer, I can confidently say that I am an ideal candidate for this role. Over the last 5 years, I have honed my AI/ML engineering expertise which includes LLM/agentic AI development and the use of AWS services like Bedrock, SageMaker, Textract and more. These experiences ensure that I have a clear understanding of how to optimize prompt engineering, retrieval-augmented generation, multi-agent communication, all while maintaining data compliance. Drawing from past projects in healthcare/Life Sciences AI solutions with regulatory compliance and my toolkit which includes monitoring tools like Prometheus and Grafana alongside AWS-native monitoring platforms we will be able to build event-driven pipeline systems for your clinical workflows that ensures high-data security measures are maintained through secure API integrations. In conclusion, if you are looking for a seasoned professional who can hit the ground running to build powerful and compliant AI/ML solutions on AWS targeted at healthcare clinica

@Fahadghouri7

With over 3 years of experience as an AI/ML engineer, I am confident I possess the right skill set for your AWS AI project. My expertise in developing agentic AI workflows, building LLM-powered agents with LangChain and AutoGen, and optimizing prompt engineering aligns perfectly with your needs. Additionally, my experience with AWS AI services such as Bedrock, SageMaker, Textract, and Comprehend Medical is an added advantage. As a detail-oriented professional, I prioritize compliance, latency and accuracy - all vital aspects to effectively implement this project. Furthermore, my knowledge in event-driven architectures using AWS Lambda, Step Functions, and EventBridge will be instrumental in streamlining your workflow. Given that your project focuses on the healthcare industry and regulatory compliance is crucial here, my previous experience in similar projects can add immense value. My coding prowess in Python/TypeScript and proficiency in Git equip me to handle complex challenges efficiently while ensuring compatibility and scalability of the codebase over time. In conclusion, not only am I deeply familiar with the tech stack you've mentioned, but my proven track record in developing innovative AI solutions seal the deal. Let's leverage AWS's cutting-edge capabilities to build transformative AI systems that redefine clinical source verification!

@Cmonosoft

Hello, I am an AI engineer with experience in building LLM based workflows using Python and AWS services such as Bedrock, Lambda, Step Functions, and EventBridge. I have worked on agent based systems, RAG pipelines, prompt optimization, and secure API integrations with a focus on performance and reliability. I am comfortable collaborating with data teams, monitoring models, and improving accuracy and latency while maintaining data safety. I can share relevant projects, availability, and discuss how I would approach your clinical verification and query generation workflows. Let's connect to discuss the relevant projects and case studies. Looking forward to hearing from you. Regards Saurabh S.

@Web1devloper

As an experienced Data Analyst and Scientist with a speciality in Machine Learning, Python, and API integrations, I believe I have the ideal skill set to excel within this AWS AI Engineer position. In my 8+ years of professional experience, I've leveraged my expertise in Python, AWS (including Bedrock), and plain old problem-solving to derive profound value from complex datasets--an ability that directly aligns with your project description. I pride myself on being able to create effective data storytelling narratives and optimized dashboards, two skills that are directly transferable to your project objective of implementing agentic AI workflows while ensuring accuracy, latency, and compliance. With me on board, not only do you gain a professional who can seamlessly integrate APIs and develop secure event-driven pipelines, but also one who possesses a deep passion for experimentation--the willingness to explore iterative improvements that can impact the bottom line positively. Let's collaborate to unlock the full potential of your clinical source verification workflows through an agile strategic data-driven approach!

@himanshus642

As an experienced Full Stack Developer specializing in AI automation and intelligent workflows, I bring strong expertise in AWS Lambda, Python, and event-driven architectures. I have built secure financial platforms and medical AI systems, ensuring high performance, regulatory compliance, and data privacy. With hands-on experience in AWS services like Lambda, Step Functions, and EventBridge, I can develop scalable, intelligent pipelines with strong accuracy and low latency. Along with technical excellence, I prioritize clear communication and timely delivery, consistently earning 5-star client feedback. I’d be glad to contribute my AI and API expertise to your project.

@SahilRao1247

With a Bachelor's in Computer Science and over six years of experience in AI/ML engineering, I am well-equipped to take on your AWS AI Engineer position. I am highly proficient in Python and TypeScript, with hands-on experience in LangChain, LlamaIndex, and AutoGen - skills that would add immense value to the project. Additionally, my familiarity with AWS AI services like Bedrock and SageMaker will ensure efficient implementation. My problem-solving mindset combined with my ability to experiment and iterate quickly will be particularly advantageous in the optimization of prompt engineering, retrieval-augmented generation (RAG), and multi-agent communication tasks. In the field of healthcare AI solutions, ensuring regulatory compliance is essential, and this is an area of experience for me that aligns perfectly with your project's context. I am confident about securing PHI/PII while developing event-driven pipelines using AWS Lambda, Step Functions, and EventBridge. My career has honed my skills in monitoring, testing, and fine-tuning AI workflows for accuracy, latency, and compliance - qualities that will be essential for maintaining the high standard expected from your clinical source verification systems. Ultimately, by hiring me as your AWS AI Engineer, you can expect thoroughness and excellence at every stage of your project. Let's make your agentic AI workflows intelligent! Best regards, Sahil

@Hemantt841

I understand you require an AWS AI Engineer to implement agentic AI workflows for clinical source verification and discrepancy detection using AWS Bedrock and open-source frameworks like LangChain and AutoGen. You also need expertise in building event-driven pipelines with Lambda, Step Functions, and EventBridge, while ensuring secure API integrations and compliance within healthcare AI solutions. With over 15 years of experience and 200+ completed projects, I specialize in AI & Automation leveraging Python and AWS cloud services. My background includes extensive work on API integrations and building scalable, event-driven architectures that align well with your need for retrieval-augmented generation and multi-agent communication optimization. To execute your project, I will design and develop LLM-powered agents integrated with AWS Bedrock, orchestrated via Lambda and Step Functions for real-time clinical data workflows. I will collaborate closely with your data engineers to ensure PHI/PII-safe ingestion pipelines and continuously monitor and fine-tune AI agents for accuracy and latency within regulatory compliance. A phased delivery over 6–8 weeks will cover development, testing, and deployment. I’m keen to explore your project further and discuss how we can achieve your goals efficiently.

@servicedigi

We bring 4+ years of backend engineering experience (Node.js, Python/FastAPI) and are actively building AI-driven systems including RAG pipelines, LLM integrations, and modular agent workflows. Your AWS AI Engineer role aligns directly with our hands-on experience in architecting production-ready AI services. Relevant Experience: • Designed RAG pipelines (chunking, embeddings, vector DB, retrieval tuning) • Built LLM-powered workflows using LangChain-style orchestration • Developed secure REST APIs for AI-agent integrations • Implemented async/event-driven processing patterns • Worked on greenfield AI systems and enhanced live production platforms AWS & Agentic Architecture Approach: • Bedrock-based LLM orchestration with modular agent layers • Lambda + Step Functions for multi-step AI workflows • EventBridge-driven event pipelines • PHI/PII-aware data flow design (tokenization, access control, logging) • Prompt optimization, evaluation loops, latency monitoring We focus on clean architecture, scalability, and compliance-ready AI systems — especially where accuracy and auditability matter (e.g., clinical workflows). Happy to outline a proposed AWS architecture (Bedrock + RAG + event-driven pipeline), confirm timeline, and discuss how we’d structure multi-agent coordination for discrepancy detection and query generation.

@krutarthp2

We are a highly experienced and professional development team specializing in delivering high-quality digital solutions. Our expertise includes: • Web Development • MERN Stack Development • Full Stack Development • Mobile Application Development • Java Development • Node.js Development • Python Development We have successfully completed multiple projects across various technologies and industries. Our team consists of experienced developers who focus on quality, performance, and client satisfaction. We believe in clear communication, timely delivery, and building long-term professional relationships. Connect with us once, and we guarantee you will be satisfied with our work and dedication. Let’s build something great together.

@karthikresonite

Hello, Resonite Technologies has a proven AI engineering team with deep hands-on experience in AWS-native, agentic AI systems—especially in regulated environments like Healthcare & Life Sciences. We can deliver: ✔ Agentic AI workflows for clinical source verification, discrepancy detection & intelligent query generation ✔ LLM-powered agents using AWS Bedrock, LangChain, AutoGen & LlamaIndex ✔ Secure, event-driven pipelines using Lambda, Step Functions & EventBridge ✔ RAG optimization, prompt engineering & multi-agent orchestration ✔ PHI/PII-safe ingestion pipelines aligned with HIPAA/GxP compliance ✔ Integration with external systems via secure APIs ✔ Monitoring, evaluation & fine-tuning for accuracy, latency & auditability Our team has strong Python/TypeScript expertise and real-world experience with Bedrock, SageMaker, Textract & Comprehend Medical. We follow compliance-first architecture with encryption, IAM hardening, and audit logging. We bring a solution-driven mindset—rapid experimentation, measurable benchmarks, and production-ready deployments on AWS. Let’s discuss your clinical AI vision and build a scalable, compliant solution. Best Regards, Resonite Technologies

@dsingla2308

Hi, I’m an AI-focused developer with strong experience in AWS and Python, and your AWS AI Engineer role is a great fit for my skills. I’ve built LLM-powered workflows and integrated AI systems into real applications, focusing on reliability, performance, and security. I’ve worked with AWS services like Lambda, Step Functions, EventBridge, and Bedrock, as well as frameworks like LangChain and LlamaIndex, to create agent-based workflows, RAG pipelines, and multi-agent communication. I’m comfortable optimizing prompts, improving model outputs, and connecting AI agents to external APIs. I also understand the importance of handling sensitive data securely and have experience building systems that manage PII/PHI safely while staying compliant. I take an iterative approach — testing, refining, and improving AI workflows to get the best results. I’d love to connect to discuss how I can help build and optimize your AI workflows on AWS and contribute to your team’s success. Best regards, Deepak

@singhajitm

Hi, I have 6 years of backend development on python and have completed RAG and AI based implementation in my organization. I have properly read the description and requirement and will be start working on the project immediately. I'm also willing to negotiate on the budget as well.

@dibyajyotid90

I assure you that I will dedicate myself wholeheartedly to the completion of this project, exerting every effort to ensure its successful conclusion. I am fully committed to seeing this endeavor through to the end, and I will apply my skills and abilities diligently in order to achieve the desired outcome.

@shyamk734

I’m a Cloud & Infrastructure Architect with 7+ years of experience designing and governing enterprise-scale multi-cloud platforms across AWS, GCP, OCI, and Azure. I specialize in high-availability architecture, hybrid networking, security governance, SRE-driven reliability, and FinOps optimization. In my current role at Accenture, I’ve led multi-cloud landing zone design, reduced downtime by 45%, delivered 30%+ cost optimization (~$180K savings), and strengthened audit compliance in regulated environments.

@manasranjanm3

Hello, I’m very interested in your AWS Engineer project and would love to help you design, deploy, and optimize your AWS infrastructure. I have strong hands-on experience with AWS Lambda, serverless architecture, API Gateway, S3, EC2, ECS/EKS, IAM, and CloudWatch, along with Infrastructure-as-Code using Terraform and CloudFormation. I specialize in building scalable, secure, and cost-efficient cloud solutions. I can help review your current setup, implement event-driven serverless workflows, automate deployments through CI/CD pipelines, and ensure high availability with proper monitoring, logging, and security best practices. Beyond deployment, I focus on long-term reliability, performance optimization, and cost control. I also provide clear documentation and ongoing support to ensure smooth operations. I would be happy to understand your requirements and propose the best architecture and implementation plan. Looking forward to working with you. Best regards, Manas