--- title: "Hire AWS Bedrock & AgentCore Developers | Vindler" description: "Hire senior AWS Bedrock and AgentCore developers for enterprise AI on AWS. We build production LLM applications with Bedrock, SageMaker, Lambda, and AgentCore for scalable, secure AI deployments." url: "https://vindler.solutions/hire/aws-bedrock-developers" locale: "en" updatedAt: "2026-11-12" --- # Enterprise AI on AWS with Bedrock & AgentCore AWS Partner Network members who build production AI systems on Bedrock, not just proof-of-concepts. We integrate Claude, Llama, and Titan models with your existing AWS infrastructure through AgentCore, Lambda, SageMaker, and the services your team already knows. Tell Us About Your Project Technology Partners [AWS Partner Network](https://aws.amazon.com/partners/)[LangChain](https://www.langchain.com/) Recognized by Clutch [Top Clutch AI Consulting Company Brazil 2026](https://clutch.co/profile/vindler-solutions)[Top Clutch AI Company Brazil 2026](https://clutch.co/profile/vindler-solutions)[Top Clutch AI Company São Paulo 2026](https://clutch.co/profile/vindler-solutions)[Top Clutch Chatbot Company Brazil 2026](https://clutch.co/profile/vindler-solutions) ## What We Build with AWS Bedrock & AgentCore From Bedrock integration to multi-agent systems on AgentCore, we deliver enterprise AI solutions on AWS that scale. ### Bedrock LLM Integration Production applications using Claude, Llama, Titan, and other foundation models through AWS Bedrock. We handle model selection, prompt optimization, streaming responses, guardrails configuration, and the IAM policies that keep your AI deployments secure within your AWS organization. ### AgentCore Multi-Agent Systems Build and deploy AI agents with AWS AgentCore that coordinate across your enterprise systems. We design agent architectures with tool use, memory, and orchestration that scale automatically and integrate with your existing AWS services. ### Enterprise AI Security & Compliance AI deployments that meet enterprise security requirements. We implement VPC endpoints for Bedrock, KMS encryption for model inputs and outputs, CloudTrail logging for audit compliance, and Bedrock Guardrails to prevent prompt injection and harmful content. ### Serverless AI Pipelines Event-driven AI processing with Lambda, Step Functions, and Bedrock. We build serverless architectures that process documents, classify content, generate summaries, and route decisions at scale without managing infrastructure. ### Knowledge Bases & RAG on Bedrock Production RAG systems using Bedrock Knowledge Bases with OpenSearch, Aurora, or Pinecone as vector stores. We handle document ingestion, chunking strategies, embedding model selection, and retrieval optimization for accurate, sourced AI responses. ### Model Fine-Tuning & Customization Custom model training on SageMaker with deployment through Bedrock. We handle data preparation, training infrastructure, evaluation pipelines, and A/B testing between base and fine-tuned models to validate improvements before production rollout. Built by Senior Engineers ## Why AWS AI Projects Need Senior Cloud Engineers AWS Bedrock makes it easy to call an LLM. Making it production-ready on AWS is a different challenge entirely. You need IAM policies that follow least-privilege without blocking your AI pipeline. You need VPC endpoints so model traffic stays off the public internet. You need KMS encryption for data at rest and in transit. You need CloudTrail logging that satisfies your compliance team. And you need all of this to work together without turning your deployment into a three-month security review. AgentCore is AWS's answer to multi-agent orchestration, but it is new and the documentation is sparse. Most teams that try it end up with fragile agent workflows that break under load or accumulate costs they did not expect. We have built agent architectures on AWS that handle thousands of requests daily, with proper error handling, cost controls, and the observability needed to debug agent decisions in production. As AWS Partner Network members, we have direct access to AWS solution architects and early access to new services. When you hit a limitation in Bedrock or AgentCore, we know whether it is a configuration issue, a known limitation with a workaround, or something we need to escalate to the AWS team. This access saves weeks of debugging and dead ends. ## Our Tech Stack We work across the AWS AI ecosystem and integrate with the tools your team already uses. AWS Bedrock AWS AgentCore AWS SageMaker AWS Lambda AWS Step Functions AWS OpenSearch AWS IAM AWS KMS AWS CloudTrail Python LangChain Anthropic Claude Meta Llama Amazon Titan FastAPI Terraform CDK ## AWS AI Projects We Have Delivered Real results from production AWS Bedrock deployments. [35% increase in customer satisfaction ### AI Sales Assistant on AWS Built a Bedrock-powered sales assistant with RAG using Knowledge Bases and OpenSearch. Deployed on Lambda for serverless scaling with full CloudTrail audit logging for enterprise compliance. Read Case Study](https://vindler.solutions/case-studies/ai-sales-assistant-rag)[90% automation rate ### Multi-Agent System on AgentCore Designed a multi-agent architecture on AWS AgentCore where specialized agents handle research, analysis, and reporting. Integrated with existing AWS services through IAM roles and VPC endpoints. Read Case Study](https://vindler.solutions/case-studies/multi-agent-systems-architecture)[Revenue optimization with ML ### AI-Powered Dynamic Pricing Built a dynamic pricing system using SageMaker for model training and Bedrock for real-time inference. Lambda functions process pricing decisions at scale with sub-second latency. Read Case Study](https://vindler.solutions/case-studies/dynamic-pricing-system) ## How We Work A straightforward process from first call to production deployment. Step 1 ### Discovery Call We start with a 30-minute technical conversation to understand your data, your users, and your constraints. No sales pitch. We dig into what you have tried, what failed, and what success looks like. Step 2 ### Architecture Proposal Within a week, we deliver a detailed technical proposal: system architecture, technology choices with rationale, estimated timeline, and cost breakdown. You will know exactly what we plan to build and why. Step 3 ### Build & Ship We build iteratively with weekly demos. You see working software from week one, not slide decks. Every PR is reviewed, every decision is documented, and we transfer knowledge continuously so your team can maintain what we build. ## Frequently Asked Questions ### ### ### ### ### ### ### ## Ready to Build Enterprise AI on AWS? Tell us about your AWS AI project and we will respond within 24 hours with an initial assessment. Whether you need Bedrock integration, AgentCore agents, or help migrating existing AI to AWS. Free 30-minute discovery call AWS architecture proposal within one week Working prototype in the first sprint ### Get a Free Assessment Describe your AWS AI project and we'll assess how Bedrock and AgentCore can power your enterprise AI. ## Structured data ```json {"@context":"https://schema.org","@type":"Organization","@id":"https://vindler.solutions/#organization","name":"Vindler Solutions","alternateName":"Vindler","legalName":"Vindler Desenvolvimento de Sistemas de IA Ltda - EPP","url":"https://vindler.solutions","logo":"https://vindler.solutions/logo.png","description":"Vindler is a global AI engineering consultancy specializing in custom AI solutions, LLM integration, and enterprise-grade AI systems.","foundingDate":"2025-06-02","foundingLocation":{"@type":"Place","name":"São Paulo, Brazil"},"taxID":"61.102.920/0001-05","email":"contact@vindler.solutions","telephone":"+1-646-846-5339","numberOfEmployees":{"@type":"QuantitativeValue","minValue":1,"maxValue":10},"areaServed":[{"@type":"Country","name":"United States"},{"@type":"Place","name":"Europe"},{"@type":"Country","name":"Brazil"}],"knowsAbout":["Multi-agent systems","Retrieval-augmented generation","Voice AI agents","LangChain","LangGraph","LiveKit","AWS Bedrock","Model Context Protocol","LLM observability and evaluation"],"founder":{"@type":"Person","@id":"https://vindler.solutions/about#carlos-dutra","name":"Carlos Dutra","jobTitle":"Founder and CEO","url":"https://vindler.solutions/about","sameAs":["https://www.linkedin.com/in/carlosdutra","https://github.com/cdutr"]},"contactPoint":{"@type":"ContactPoint","contactType":"Customer Support","email":"contact@vindler.solutions","telephone":"+1-646-846-5339","url":"https://vindler.solutions/contact","availableLanguage":["English","Portuguese","Spanish"]},"address":[{"@type":"PostalAddress","addressLocality":"São Paulo","addressRegion":"SP","addressCountry":"BR","streetAddress":"Av. 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API calls to OpenAI send your data to a third-party server. For enterprises with data residency requirements, compliance obligations, or sensitive data, Bedrock provides the same foundation models (Claude, Llama) with AWS-grade security: IAM access control, KMS encryption, VPC endpoints, and CloudTrail audit logging. You also get consolidated billing through your existing AWS agreement and avoid managing separate API keys and rate limits."}},{"@type":"Question","name":"What is AWS AgentCore and when should we use it?","acceptedAnswer":{"@type":"Answer","text":"AgentCore is AWS's managed service for building, deploying, and scaling AI agents. It provides agent orchestration, tool integration, memory management, and automatic scaling. Use AgentCore when you need AI agents that interact with AWS services (S3, DynamoDB, Lambda), when you want managed infrastructure instead of self-hosted agent frameworks, or when your compliance requirements mandate that all AI processing stays within AWS. For simpler use cases, direct Bedrock API calls may be sufficient."}},{"@type":"Question","name":"How do you handle Bedrock costs and model selection?","acceptedAnswer":{"@type":"Answer","text":"We implement model routing: simple tasks use cheaper models (Titan, Haiku) while complex reasoning uses more capable models (Claude Sonnet, Opus). We add semantic caching to avoid repeated inference for similar queries, set up CloudWatch alarms for spending thresholds, and use provisioned throughput for predictable workloads. We track cost per request in production and optimize prompts to minimize token usage. Most clients see 30-50% cost reduction after optimization."}},{"@type":"Question","name":"Can you migrate our existing AI application to AWS Bedrock?","acceptedAnswer":{"@type":"Answer","text":"Yes. We have migrated applications from direct OpenAI API calls, Azure OpenAI, and self-hosted models to Bedrock. The migration involves updating API calls to use the Bedrock SDK, configuring IAM roles and VPC networking, setting up Guardrails for content safety, and validating that model outputs meet your quality benchmarks. We run the old and new systems in parallel during migration to ensure no quality regression."}},{"@type":"Question","name":"How do you secure AI applications on AWS?","acceptedAnswer":{"@type":"Answer","text":"We follow AWS Well-Architected Framework principles for AI workloads. This means IAM roles with least-privilege access (not API keys), VPC endpoints for Bedrock to keep traffic private, KMS encryption for all data, CloudTrail logging for audit trails, and Bedrock Guardrails for content filtering and prompt injection prevention. We also implement application-level security: input validation, output sanitization, and rate limiting to prevent abuse."}},{"@type":"Question","name":"Do you work with SageMaker for custom model training?","acceptedAnswer":{"@type":"Answer","text":"Yes. When foundation models need customization, we use SageMaker for fine-tuning and custom model training. We handle data preparation, training infrastructure (including distributed training on multi-GPU instances), hyperparameter optimization, model evaluation, and deployment through Bedrock custom model import. We also build evaluation pipelines that compare fine-tuned models against base models to validate that the customization actually improves performance on your specific use case."}},{"@type":"Question","name":"What AWS certifications does your team hold?","acceptedAnswer":{"@type":"Answer","text":"Our team includes AWS Certified Solutions Architects and we are members of the AWS Partner Network. Beyond certifications, we have practical experience deploying AI systems on AWS across multiple industries with real compliance requirements. We know the difference between what AWS documentation says and what actually works in production, especially for newer services like Bedrock and AgentCore."}}]} ```