Principal AI Engineering Architect

🕒 Julho 29

🇺🇸 Estados Unidos – Remoto (EUA)

💵 $180.375 - $230.625 / ano

⏰ Tempo Integral

🔴 Especialista

🤖 Engenheiro de IA

👻 Score fantasma 4%

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Robots & Pencils

SiteLinkedInTodas as Vagas

51 - 200 funcionários

🤖 Inteligência Artificial

🤝 B2B

☁️ SaaS

💰 Venture Round em 2022-04

Artificial Intelligence • B2B • SaaS

A Robots & Pencils é uma empresa de inovação digital especializada no desenvolvimento de estratégias digitais e produtos utilizando tecnologias móveis, web e de ponta para impulsionar a transformação das empresas. Eles se concentram em áreas como desenvolvimento móvel, design de produto, pesquisa de UX, inteligência artificial, machine learning e gestão de mudanças organizacionais. Com o compromisso de combinar criatividade com tecnologia, eles visam desbloquear insights de dados e aprimorar a inovação em produtos, entregando, assim, excelentes experiências aos clientes e ajudando as marcas a obter uma vantagem competitiva.

Descrição

• Define technical strategy and lead architectural design across cloud, data, and AI/ML systems for end-to-end engagements, owning architecture decisions and driving solutions from research through production at scale • Architect and ship production-grade multi-agent agentic AI systems, including agent orchestration, tool use, memory, and inter-agent communication patterns • Design and build with Amazon Bedrock AgentCore and complementary AWS GenAI services to deploy, scale, and operate agentic workloads securely in production • Architect scalable cloud-native solutions with a strong bias toward AWS, including multi-cloud and hybrid strategies where needed (AWS primary, with Azure, GCP, Kubernetes as secondary) • Design data architectures including warehouses, data lakes, and pipelines for batch and streaming workloads (e.g., Snowflake, Redshift, BigQuery, Spark, Kafka) • Design AI/ML systems including model serving, MLOps pipelines, feature stores, and LLM-based applications (e.g., SageMaker, Bedrock, AgentCore, Vertex AI, MLflow, Hugging Face) • Build and evolve scalable ML platforms, pipelines, and infrastructure that support reliable, repeatable model development and deployment across teams • Define infrastructure as code, CI/CD, and DevOps standards across engagements (e.g., Terraform, CloudFormation, GitHub Actions) • Drive performance, scalability, cost, and reliability optimization across deployed systems • Ensure architecture meets security, governance, and compliance requirements (e.g., GDPR, HIPAA, SOC2) • Lead cloud migrations and platform modernization initiatives • Set the standard for AI-forward engineering, using tools like Claude and Cursor with sophistication and helping the team adopt them effectively

🎯 Requisitos

• 8+ years of software engineering experience, with at least 5 years in technical leadership roles and 4+ years focused on AI/ML systems in production • Expert software engineering background (Python or similar) with strong design sensibilities for scalable, maintainable systems • Deep, hands-on expertise designing and shipping production multi-agent agentic AI systems, including agent orchestration, planning, tool use, and multi-agent coordination patterns • Deep expertise with AWS, including in-depth knowledge of AWS GenAI offerings and hands-on experience with Amazon Bedrock AgentCore; broader multi-cloud experience (Azure, GCP) is a plus • Strong background in microservices, serverless, containers, and event-driven systems (e.g., Kubernetes, Docker, Lambda, EventBridge) • Proficiency with infrastructure as code and CI/CD (e.g., Terraform, CloudFormation, Pulumi, GitHub Actions) • Strong data architecture expertise across relational, NoSQL, and big data systems (e.g., PostgreSQL, MongoDB, Snowflake, BigQuery, Spark, Kafka) • Hands-on experience with data modeling, ETL/ELT pipelines, and orchestration (e.g., Airflow, Prefect, dbt) • Mastery of AI frameworks and orchestration tools for building agentic systems (e.g., LangChain, LangGraph, AgentCore, CrewAI, AutoGen, or equivalents) • Strong experience designing AI/ML systems for production, including LLMs, MLOps, and model serving (e.g., SageMaker, Bedrock, Vertex AI, MLflow, Hugging Face, PyTorch, TensorFlow) • Strong experience with evaluation frameworks and observability tools for LLM and agentic apps, including building these capabilities where they don't yet exist • Deep understanding of AI safety, responsible AI principles, prompt injection defenses, and PII handling • Extensive experience building RAG pipelines: chunking strategies, embedding models, vector databases, and advanced retrieval techniques • API design experience, including architecting and integrating with internal and third-party services at scale • Advanced cost optimization expertise: token economics, caching strategies, model routing, quantization • Solid understanding of networking, security, identity, and access management in cloud environments • Experience with governance, compliance, and observability frameworks • Track record of senior technical leadership and mentoring experienced engineers • Strong stakeholder communication skills, with the ability to translate technical depth across audiences • Demonstrable, day-to-day usage and expert knowledge of AI-forward coding tools such as Claude Code and Cursor • Multi-cloud architecture experience, AI ethics or responsible AI experience, or enterprise architecture certifications (e.g., TOGAF, AWS/Azure/GCP) is a plus.