--- title: "Hire Senior AI Engineers & Developers | Vindler" description: "Hire senior AI engineers and developers for production LLM applications, RAG systems, and intelligent automation. Remote AI contractors and consultants who understand every line they ship." url: "https://vindler.solutions/hire/ai-engineers" locale: "en" updatedAt: "2026-11-12" --- # Hire Senior AI Engineers for Production Systems From LLM integration to multi-agent architectures, our senior AI developers build systems that work beyond the demo. We are software engineers who specialize in AI, understanding every line we ship. Tell Us About Your Project 7 production AI systems delivered  ·  AWS Partner 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) Carlos Dutra, Founder of Vindler Who you work with ## Carlos Dutra, Founder Vindler is led by a senior engineer, not a sales team. Carlos has spent 15+ years building and leading data and AI systems, holds an MSc in Applied Mathematics (machine-learning research) from USP, and completed MIT Sloan Executive Education. He has led teams at Wildlife Studios and Trustly, ships production AI on AWS, and contributes to open source. A Toptal Verified Expert since 2020. MSc, Universidade de São PauloMIT Sloan Executive EducationToptal Verified Expert15+ years engineeringHugging Face Diffusers contributor [Quoted in VentureBeat on how enterprises should optimize for AI-referred traffic.](https://venturebeat.com/technology/llm-referred-traffic-converts-at-30-40-and-most-enterprises-arent-optimizing) Experience across Wildlife Studios Trustly Typeform Toptal Selected work ## Production systems, real outcomes A few engagements in depth, with the numbers that matter. Multi-Agent Systems Architecture Enterprise AI ### Multi-Agent Systems Architecture A production supervisor-worker multi-agent assistant for a form-building platform - Production multi-agent assistant: six specialized agents and 90+ backend tools over MCP - Reusable agent framework (shared graph, A2A, MCP, human-in-the-loop) that scales by adding agents - Durable human-in-the-loop approvals that survive container restarts LangGraphAWS Bedrock AgentCoreA2A ProtocolMCPOpenAI GPT Named reference available on request. [Read the full case study](https://vindler.solutions/case-studies/multi-agent-systems-architecture) Voice AI Assistant for Medicare Patients Healthcare ### Voice AI Assistant for Medicare Patients A voice-first companion for elderly patients on bedside tablets - Runs in production on kiosk tablets with end-to-end observability on every call - True voice-and-touch multimodal interface designed for elderly accessibility - Six voice skills (medication, reminders, weather, news, trivia, word games) plus web search LiveKitAssemblyAIOpenAI GPT-4.1CartesiaSilero VAD Named reference available on request. [Read the full case study](https://vindler.solutions/case-studies/medicare-voice-assistant) Autonomous Feature-Generation Pipeline for Mobile Gaming Mobile Gaming ### Autonomous Feature-Generation Pipeline for Mobile Gaming From a one-line brief to designed, built, and tested game features - Autonomous phases (with human approval gates) from brief to designed, built, and tested feature - Five-layer verification stack; a runtime integration contract caught 5 gameplay bugs every visual check missed - Pilot: a feature's art set generated and machine-validated in under an hour versus a ~2-hour-per-asset manual baseline Claude Agent SDKMCPUnityBlenderGenerative AI Named reference available on request. [Read the full case study](https://vindler.solutions/case-studies/generative-3d-game-assets) AI-Powered Sales Assistant with RAG Automotive / Sales ### AI-Powered Sales Assistant with RAG A production RAG and analytics assistant for automotive dealers - Shipped to production on Kubernetes across CPU and GPU fleets with GitOps delivery - Hard multi-tenant isolation: dealer-scoped SQL validation blocks cross-dealer data access - Grounded RAG with an anti-hallucination fallback instead of fabricated answers AWS BedrockpgvectorBigQueryClaudeSegment Anything Named reference available on request. [Read the full case study](https://vindler.solutions/case-studies/ai-sales-assistant-rag) [See all case studies](https://vindler.solutions/case-studies) ## What We Build with AI From RAG prototypes to production multi-agent systems, we deliver AI solutions that scale. ### Custom LLM Applications End-to-end AI applications built on OpenAI, Anthropic Claude, AWS Bedrock, and open-source models. We handle prompt engineering, output parsing, streaming, caching, and fallback strategies so your AI features work reliably under production load. ### Production RAG Systems Retrieval-augmented generation that delivers accurate, sourced answers from your data. We build the full pipeline: document ingestion, chunking strategies, embedding optimization, hybrid search, re-ranking, and citation tracking. ### Multi-Agent Systems Coordinated AI agents that handle complex workflows through LangGraph and custom orchestration. We build stateful systems with conditional routing, tool use, human-in-the-loop checkpoints, and error recovery. ### AI-Powered Automation Replace manual processes with intelligent automation. We build AI systems that classify, extract, summarize, and route information, handling the edge cases and validation that make automation trustworthy. ### AI Analytics & Intelligence Transform raw data into actionable insights using LLMs. We build AI-powered dashboards, anomaly detection systems, and predictive models that help your team make better decisions faster. ### AI Security & Guardrails Production AI needs guardrails. We implement prompt injection protection, output validation, content filtering, PII detection, and access controls so your AI systems are safe for enterprise deployment. Built by Senior Engineers ## Why Senior AI Engineers Matter More Than Ever AI tooling changes weekly. New models drop, APIs break, frameworks pivot. A junior developer following last month's tutorial builds software that is already outdated. Senior AI engineers understand the fundamentals beneath the hype: how attention mechanisms work, why retrieval quality degrades, when fine-tuning beats prompt engineering, and how to evaluate model outputs systematically. The gap between an AI demo and a production system is where most projects die. Demos cherry-pick inputs that make the model look good. Production systems handle the inputs your users actually send: ambiguous queries, adversarial prompts, edge cases in languages the model barely supports, and the inevitable 3 AM when the API provider has an outage. Building for production means building for failure. We have shipped AI systems across automotive, healthcare, e-commerce, financial services, and enterprise SaaS. We know which patterns work, which abstractions to avoid, and how to build evaluation pipelines that catch regressions before your users do. When you hire our team, you get engineers who have already made the expensive mistakes so you do not have to. ## Our Tech Stack We work across the AI ecosystem and integrate with the tools your team already uses. Python TypeScript LangChain LangGraph FastAPI Next.js OpenAI Anthropic Claude AWS Bedrock AWS Lambda Pinecone Qdrant Chroma LangFuse LangSmith Docker Kubernetes ## 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 ### ### ### ### ### ### ### ### Our engineers work from São Paulo. Rates, time zones and contracting for a team in Brazil are covered in [nearshore software development in Brazil](https://vindler.solutions/blog/ai-development-nearshore-brazil). ## Ready to Build Production AI Systems? Tell us about your project and we will respond within 24 hours with an initial assessment. No commitment, no pressure, just a technical conversation about what is possible. Free 30-minute discovery call Detailed architecture proposal within one week Working software from week one of engagement ### Get a Free Assessment Describe your AI project and we'll send you an initial technical assessment within 24 hours. ## 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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We are model-agnostic and choose the right tool for each use case based on performance, cost, latency, and data privacy requirements. For specialized tasks, we also work with open-source models through Hugging Face and vLLM."}},{"@type":"Question","name":"How is hiring an AI agency different from hiring freelance AI developers?","acceptedAnswer":{"@type":"Answer","text":"A freelance AI developer gives you one person with one perspective. An agency gives you a team with complementary skills: AI engineers, backend developers, infrastructure specialists, and a technical lead who has delivered dozens of AI projects. We also provide continuity. If an engineer is sick or leaves, your project does not stop. We handle code review, architecture decisions, and knowledge transfer so you are never dependent on a single person."}},{"@type":"Question","name":"Can you work as a remote AI development team?","acceptedAnswer":{"@type":"Answer","text":"Yes. Our team works remotely across time zones. We overlap with US Eastern hours for daily standups and async communication covers the rest. We use shared repositories, detailed PR descriptions, and weekly demo sessions so you always know what is being built and why. Many of our clients have never met us in person but have shipped multiple production AI systems with our team."}},{"@type":"Question","name":"Do you offer part-time or fractional AI engineering?","acceptedAnswer":{"@type":"Answer","text":"Yes. Not every project needs a full-time team. We offer part-time engagements starting at 20 hours per week, ideal for startups that need senior AI expertise but cannot justify a full-time hire. We also offer fractional CTO services for companies that need strategic AI leadership without the executive salary."}},{"@type":"Question","name":"How do you handle AI model costs and optimization?","acceptedAnswer":{"@type":"Answer","text":"We treat LLM costs as a first-class engineering concern. We implement token budgets, caching layers, model routing (using cheaper models for simple tasks and expensive models for complex ones), and prompt optimization to minimize token usage without sacrificing quality. We track cost per request in production and set up alerts for spending anomalies. Most clients see 40-60% cost reduction after we optimize their existing AI pipelines."}},{"@type":"Question","name":"What does your AI development process look like?","acceptedAnswer":{"@type":"Answer","text":"We start with a discovery call to understand your use case, data, and constraints. Within a week, we deliver a technical proposal with architecture, timeline, and cost breakdown. Development is iterative with weekly demos of working software. We ship to production early and often, with full observability from day one. Every PR is reviewed, every decision is documented, and we transfer knowledge continuously."}},{"@type":"Question","name":"How do you evaluate and test AI systems?","acceptedAnswer":{"@type":"Answer","text":"We build automated evaluation pipelines that run before every deployment. This includes golden dataset testing (known input-output pairs), retrieval quality metrics (precision, recall, MRR), LLM output quality scoring (relevance, faithfulness, coherence), latency benchmarks, and cost tracking. We also implement A/B testing frameworks for comparing prompt strategies and model versions in production."}},{"@type":"Question","name":"What industries have you built AI solutions for?","acceptedAnswer":{"@type":"Answer","text":"We have delivered AI systems for automotive (AI sales assistants), healthcare (voice AI for Medicare patients), e-commerce (product recommendation), financial services (document analysis and compliance), enterprise SaaS (workflow automation and internal knowledge bases), mobile gaming (live ops content automation and player analytics), and education (content generation). Each industry has specific requirements around data privacy, latency, accuracy, and regulatory compliance."}}]} ```