Principal AI Architect

🕒 Julho 27

🌽 Illinois – Remoto

🌽 Illinois – Remote

⏰ Tempo Integral

🔴 Especialista

🤖 Engenheiro de IA

👻 Score fantasma 12%

O que significa: quão provável esta vaga está aberta sem contratação ativa.Como ler: 60% ou mais significa que achamos que é uma vaga fantasma. Pontuações mais baixas preocupam menos.Como pontuamos: tempo em aberto, republicações, vagas abertas vs tamanho do time, rapidez para fechar vagas, e se o salário está divulgado.Observação: é uma estimativa de dados públicos, não um julgamento da empresa. Vagas reais podem ter pontuação alta, então use como uma dica, não como um fato.

Candidatar-se

Encontrar Vagas Remotas Similares

Configurar Alerta de Email para Novas Vagas

📊 Verifique sua pontuação de currículo para esta vaga

Melhore suas chances de conseguir uma entrevista verificando sua pontuação de currículo antes de se candidatar.

Enviar Currículo

Paradigm

SiteLinkedInTodas as Vagas

1001 - 5000 funcionários

Fundada em 1991

☁️ SaaS

💰 Private equity em 2025-08

SaaS

Paradigm é uma empresa cuja aplicação web de acesso público retornou apenas a mensagem: "Carregando aplicação... Seu navegador deve ter o JavaScript habilitado para que esta aplicação seja exibida corretamente. " Nenhuma informação adicional sobre seus produtos, serviços ou foco de mercado foi disponível a partir do conteúdo fornecido. Com base na presença de uma aplicação web mas sem mais detalhes, nenhum produto, setor ou clientela específica pode ser determinado a partir das informações fornecidas.

Descrição

• Architect and deliver end-to-end AI, Generative AI, and agentic AI solutions from concept through production • Apply hands-on expertise to build LLM-based systems, RAG pipelines, AI agents, and multi-agent orchestration solutions • Design AI platform capabilities including model selection, LLM routing, retrieval strategies, memory systems, and tool/function orchestration • Lead hands-on prototyping and proof-of-concepts to validate technologies and accelerate adoption • Ensure AI solutions are designed for performance, scalability, observability, privacy, and operational readiness • Define and drive architecture across multiple domains/business segments, ensuring alignment with enterprise strategy • Partner with business and technology leadership to shape AI roadmap, priorities, and execution strategy • Establish and promote architecture standards, reusable patterns, and best practices • Drive modernization initiatives to reduce technical debt and improve scalability, resilience, and performance • Implement and guide AI governance, security, responsible AI, and compliance practices • Ensure AI solutions are designed for performance, observability, privacy, and operational readiness • Collaborate across engineering, data, product, and business teams to deliver production-grade AI solutions • Mentor engineers and architects and effectively communicate AI concepts to technical and non-technical stakeholders.

🎯 Requisitos

• 10+ years of experience in software engineering, architecture, and enterprise system design. • Proven experience delivering end-to-end AI/ML and Generative AI solutions in production environments. • Strong hands-on engineering capability with ability to operate across architecture, design, and implementation. • Deep expertise in LLMs, prompt engineering, RAG, embeddings, vector databases, and agent-based systems • Experience with agent frameworks and orchestration including multi-agent patterns and integrations • Strong programming experience in Python and building APIs, microservices, and distributed systems. • Experience designing and implementing solutions on cloud platforms (Azure preferred). • Experience with DevOps practices, including CI/CD, containerization, and scalable deployment of AI systems. • Familiarity with infrastructure-as-code (Terraform, Bicep) and Kubernetes-based deployments. • Strong understanding of data architecture and integration patterns supporting AI workloads. • Ability to evaluate emerging technologies and translate them into enterprise-scale capabilities • Solid knowledge of AI governance, risk, compliance, privacy, and responsible AI principles • Strong communication and stakeholder management skills. • Ability to influence decisions across engineering, data, and business teams. • Proven ability to mentor, guide, and elevate engineering and architecture teams. • Master’s or Bachelor’s degree in Computer Science, Engineering, Data Science, or a related STEM field.