Hire the Best AWS Kinesis Developers

I help enterprises move AI from prototype to production — solving the problems that appear when AI systems become **expensive, slow, unreliable, and difficult to scale.** With 12+ years across Software Engineering, Technical Leadership, CTO, and AI Architecture, I design production-grade AI systems, agentic workflows, enterprise RAG platforms, and AI-native SaaS products. My focus is not simply building chatbots. I solve the engineering problems behind reliable AI: • Runaway token costs • Slow agent execution • Excessive LLM calls and agent loops • Poor RAG retrieval and hallucinations • Chunking and embedding problems • Context-window and memory problems • Unreliable multi-agent systems • AI infrastructure and scaling • Observability, evaluation and cost control ━━━━━━━━━━━━━━━━━━━━━━ 🚀 AI AGENT ARCHITECTURE I design production-ready: • Multi-agent systems • Planner → Supervisor → Worker architectures • Tool calling and API orchestration • MCP-based systems • Agent memory and state management • Human-in-the-loop workflows • Long-running/background agents • Event-driven agents • Agent evaluation, guardrails and failure recovery Technologies: Claude, OpenAI, AWS Bedrock, AgentCore, LangGraph, LangChain, MCP, n8n, Python, TypeScript, FastAPI, Node.js. ━━━━━━━━━━━━━━━━━━━━━━ 💰 AI TOKEN COST OPTIMIZATION AI systems can become extremely expensive at production scale. I reduce unnecessary: • Prompt/context tokens • Conversation history • RAG context • Tool outputs • Agent-to-agent communication • LLM calls and reasoning loops Using context compression, prompt caching, model routing, retrieval optimization, structured outputs, summarization and intelligent model selection. The goal isn't simply **"use a cheaper model."** It is to reduce inference cost while maintaining quality and reliability. ━━━━━━━━━━━━━━━━━━━━━━ ⚡ AGENT LATENCY OPTIMIZATION Slow agents are often an architecture problem. I analyze: User → API → Agent → LLM → Retrieval → Tools → APIs → Database → Response And optimize: • Sequential → parallel execution • Unnecessary LLM calls • Tool-call chains • RAG/vector-search latency • Database/API bottlenecks • Network round trips • Model selection • Streaming, caching and async execution ━━━━━━━━━━━━━━━━━━━━━━ 🧠 CONTEXT ENGINEERING Many AI systems fail because the model receives the **wrong context**. I design architectures for: • Short/long-term memory • Conversation history • Retrieved knowledge • Task and agent state • Tool results • Dynamic context • Context compression and prioritization The key questions are: **What should the model know? When should it know it? How much does it actually need?** ━━━━━━━━━━━━━━━━━━━━━━ 🔎 ENTERPRISE RAG & RETRIEVAL I build RAG systems optimized for **accuracy, latency, cost, security and traceability.** I solve: • Poor retrieval and irrelevant chunks • Hallucinations • Large context windows • Slow vector search • Metadata filtering • Multi-tenant / permission-aware retrieval • Citations and provenance • Embedding and reranking problems Typical pipeline: Document → Parsing → Chunking → Embedding → Hybrid Search → Metadata Filter → Reranking → Context → LLM Technologies: Pinecone, OpenSearch, Elasticsearch, pgvector, Weaviate, FAISS. ━━━━━━━━━━━━━━━━━━━━━━ ✂️ CHUNKING & EMBEDDING OPTIMIZATION Chunking is often a hidden cause of poor RAG performance. I work with: • Fixed, sentence, paragraph and semantic chunking • Parent-child retrieval • Document/code-aware chunking • Metadata enrichment • Overlap optimization • Embedding selection • Top-K tuning • Reranking The objective isn't smaller chunks — it's creating retrieval units that preserve the meaning needed to answer the question. ━━━━━━━━━━━━━━━━━━━━━━ 🏗️ AI AGENT INFRASTRUCTURE I design infrastructure for reliable, scalable agent execution: • Agent runtime and background jobs • Queues and state/checkpointing • Retries and idempotency • Concurrency and rate limiting • Observability and tracing • Cost monitoring • Multi-tenancy and security • Failure recovery AWS: Bedrock, AgentCore, Lambda, ECS, EKS, API Gateway, ALB, SQS, EventBridge, Step Functions, DynamoDB, Aurora, S3, OpenSearch, CloudWatch. ━━━━━━━━━━━━━━━━━━━━━━ 🤖 CLAUDE CODE / AI-NATIVE ENGINEERING I use **Claude Code as an AI engineering layer**, not just a code generator. Capabilities include: • Large codebase understanding • Architecture analysis • Refactoring and modernization • Feature implementation • Debugging and test generation • Code review • Repository intelligence • MCP integrations • Engineering automation I help teams evolve from traditional development toward **AI-native software engineering.** ━━━━━━━━━━━━━━━━━━━━━━ 🔄 AI APPLICATION MODERNIZATION I help existing SaaS and enterprise applications become AI-native: **Legacy Application → APIs → AI Layer → Agents → Knowledge → Automation** Including AI copilots,

🚀 DevOps Engineer | ☁️ AWS Solutions Architect & Developer • 🏗️ Terraform • 🔄 CI/CD • 🐍 Python I’m a DevOps Engineer who enjoys building reliable and scalable systems in the cloud, mainly using ☁️ AWS, 🏗️ Terraform, 🔄 GitHub Actions, and 🐍 Python. Over the past projects I’ve worked on — including 380+ hours on Upwork — I’ve helped clients automate their infrastructure, simplify deployments, and make their systems easier to manage. My goal is always to deliver solutions that are clean, practical, and built to last — not just something that “works once.” ⚡ 🛠️ What I work with: 🏗️ Infrastructure as Code using Terraform ☁️ AWS services (Lambda, S3, EC2, Aurora, DynamoDB, API Gateway, Step Functions,etc) 🔄 CI/CD pipelines with GitHub Actions 🐍 Automation & scripting with Python I also come from a backend background (.NET / C#), which helps me understand the full picture — from application code 💻 to infrastructure 🌐 — and build solutions that actually fit real development workflows. 🤝 What you can expect: 💬 Clear communication & regular updates 🧼 Clean, maintainable infrastructure 📈 Scalable and cost-aware solutions If you need help setting up your cloud infrastructure, automating your workflows, or improving your DevOps processes — feel free to reach out. I’d be happy to collaborate! 🚀

Is your AWS platform expensive, unreliable, or difficult to deploy? I can help you simplify the architecture, reduce costs, improve security, and ship changes with confidence. I build and modernize SaaS and enterprise platforms using AWS, Go, Node.js, Terraform, serverless services, containers, and secure CI/CD pipelines. I have earned more than $100,000 across 9,500 Upwork hours. My production experience includes work for the New York Lottery, Dittofi, and BlazeStack. Recent results • Managed Terraform infrastructure across six AWS commercial and GovCloud environments • Reduced ECS Fargate costs by about $450 per month • Cut environment setup time from two days to under 30 minutes • Supported a production platform with more than 100 AWS Lambda functions • Restructured over 3,000 lines of serverless infrastructure code • Built secure authentication, SSO, RBAC, audit logging, and monitoring systems • Developed multi-tenant SaaS platforms with React, Go, Node.js, PostgreSQL, and AWS • Built Amazon Bedrock and Claude workflows with structured outputs, validation, and prompt-injection protection How I can help you • Design or modernize your AWS architecture • Build Go and Node.js APIs, microservices, and backend systems • Automate infrastructure with Terraform and CI/CD • Deploy workloads with Docker, ECS, EKS, and Kubernetes • Build serverless systems with Lambda, API Gateway, EventBridge, SQS, Cognito, and Aurora • Improve cloud security, monitoring, reliability, and cost • Integrate AI features with Amazon Bedrock and Claude You’ll get clear communication, clean implementation, and systems your team can maintain after launch. Send me your current architecture, the problems you’re facing, and the outcome you need.

I'm a certified solutions architect for Amazon Web Services with experience in full-stack software development. My typical stack for web development is a React.js front-end paired with a node.js backend hosted on AWS. For mobile development my preferred stack is React-Native but I have experience in native development with Swift for iOS and native Android development in Java. I'd love to help your project at any stage, whether it's UX design, software development, API integration, data migration, or even just bug fixes & documentation. Whether you've got a new idea for an app or need a consult for a redesign on one of your micro-service containers, let me know how I can assist!

Need a DevOps Engineer who can build secure, scalable cloud infrastructure and automate deployments with confidence? I help startups, SaaS companies, and enterprises design, modernize, and manage cloud-native platforms on AWS. From Infrastructure as Code (IaC) and CI/CD automation to Kubernetes, containerized applications, and AI infrastructure, I build reliable systems that improve deployment speed, scalability, and operational efficiency. With 8+ years of experience in Cloud Engineering, DevOps, and Platform Engineering, I deliver production-ready infrastructure that supports business growth while maintaining security, reliability, and cost optimization. Cloud & DevOps Services ✔ AWS Cloud Architecture & Infrastructure ✔ Infrastructure as Code (Terraform) ✔ CI/CD Pipeline Design & Automation ✔ Docker & Kubernetes Deployment ✔ Amazon ECS, ECR & Fargate ✔ AWS Migration & Cloud Modernization ✔ AWS Security, IAM & Secrets Manager ✔ Platform Engineering ✔ Serverless & Cloud-Native Solutions ✔ Disaster Recovery & High Availability ✔ Monitoring, Logging & Observability AI Infrastructure & MLOps ✔ AI Infrastructure Deployment ✔ MLOps & ML Pipeline Automation ✔ Retrieval-Augmented Generation (RAG) Infrastructure ✔ AWS Bedrock Integration ✔ OpenAI, Anthropic & LLM API Integration ✔ Amazon OpenSearch Serverless ✔ AI Agent Infrastructure ✔ Secure Production AI Environments DevOps Tools & Technologies Cloud: AWS, Google Cloud Platform (GCP), Microsoft Azure Infrastructure as Code: Terraform, Ansible Containers: Docker, Kubernetes, Amazon ECS, Amazon ECR CI/CD: GitHub Actions, GitLab CI, AWS CodePipeline, Jenkins Monitoring: Amazon CloudWatch, New Relic, ELK Stack Why Clients Choose Me ✔ AWS Certified DevOps Engineer – Professional ✔ 8+ years of Cloud & DevOps experience ✔ Strong background in Platform Engineering and Cloud Architecture ✔ Expertise in production-ready AI and MLOps infrastructure ✔ Focus on automation, security, scalability, and cost optimization Whether you need to modernize legacy infrastructure, automate deployments, build Kubernetes environments, implement Infrastructure as Code, or deploy AI-powered applications on AWS, I can help you create secure, scalable, and reliable cloud solutions that are ready for production.

I build full-stack products and scalable AWS infrastructure that won't break under production traffic – from backend APIs and databases to clean UIs and serverless cloud systems. You get one senior engineer handling it all, so there are no handoff delays or coordination issues. I'm AWS Certified Developer with deep expertise in cloud architecture and serverless systems. I specialize in designing cost-effective infrastructure and high-performance SaaS platforms. My clients typically launch 30–40% faster and save $5K–15K/month on infrastructure. I solve complex problems with clean, production-ready solutions. No fluff, no delays – just results that scale.