Lead AI Architect

🕒 Agosto 25

🏄 California, Colorado, +14 estados a mais – Remoto

🏄 California – Remote ⛰️ Colorado – Remote 🐊 Florida – Remote 🌽 Illinois – Remote 🗽 New York – Remote 🌲 North Carolina – Remote 🏈 Ohio – Remote 🌪️ Oklahoma – Remote 🦀 Maryland – Remote ❄️ Minnesota – Remote 🔔 Pennsylvania – Remote 🎸 Tennessee – Remote 🤠 Texas – Remote ⚔️ Virginia – Remote ☕ Washington – Remote ⛰️ West Virginia – Remote

💵 $191.000 - $255.000 / ano

⏰ Tempo Integral

🟠 Sênior

🤖 Engenheiro de IA

👻 Score fantasma 0%

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.

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Accurate Background

SiteLinkedInTodas as Vagas

1001 - 5000 funcionários

Fundada em 1997

👥 RH Tech

☁️ SaaS

🤝 B2B

💰 Private Equity Round - Accurate Background em 2020-02

HR Tech • SaaS • B2B

A Accurate Background é um fornecedor global de verificação de antecedentes para emprego que auxilia empregadores na realização de triagens pré-emprego e contínuas. A Accurate oferece serviços como verificação de antecedentes criminais, verificação de identidade, triagem de drogas e saúde, histórico de condução, consultas de crédito, I-9 e E-Verify, buscas globais, monitoramento e verificações de redes sociais através de uma plataforma móvel, API e integrações com sistemas de rastreamento de candidatos. Fundada em 1997 e de propriedade minoritária, a Accurate atende mais de 16. 000 clientes em todo o mundo, realiza mais de 60 milhões de buscas anuais, suporta múltiplas indústrias (saúde, varejo, transporte, recrutamento, serviços financeiros, marketplaces de trabalho temporário) e enfatiza a conformidade com as regulamentações globais de dados e privacidade.

Descrição

• Lead the architecture, design, and technical direction for AI-enabled solutions, including AI agents, tools, GenAI-powered applications, and reusable AI services • Define enterprise AI architecture standards, reusable patterns, reference architectures, and engineering guardrails • Establish foundational AI Center of Excellence standards for scalable, secure, responsible, and production-ready AI adoption • Architect and guide development of an AI lab for experimentation, prototyping, evaluation, model testing, and rapid iteration • Define and operationalize AI-DLC practices covering experimentation, evaluation, governance, deployment, monitoring, and continuous improvement • Design reusable and scalable AI platforms, services, APIs, orchestration patterns, and integration layers • Partner with business and technology leaders to identify, prioritize, and deliver AI use cases that drive operational efficiency and measurable business value • Define architecture patterns for RAG, prompt engineering, agent orchestration, tool calling, memory management, and human-in-the-loop workflows • Architect AI agent ecosystems, tool integrations, and orchestration workflows across enterprise platforms and systems • Provide technical direction on LLMs, SLMs, embeddings, vector search, model APIs, model selection, and AI service integration • Create architecture blueprints, technical designs, reusable frameworks, decision records, and implementation standards • Ensure AI solutions are secure, observable, maintainable, compliant, and aligned to enterprise architecture principles • Establish and enforce AI governance practices covering responsible AI, data protection, privacy, compliance, auditability, and risk controls • Guide deployment, monitoring, troubleshooting, and operational readiness of AI applications and platforms • Define evaluation frameworks, quality benchmarks, feedback loops, and AI performance measurement approaches • Partner with stakeholders to move AI ideas from concept through architecture, experimentation, production, and scale • Mentor engineers, architects, and product teams on AI-native architecture, AI engineering practices, and responsible AI solution design • Influence technology selection and platform strategy across AWS, Azure, AI-native PaaS services, agent frameworks, observability tools, and enterprise integration patterns

🎯 Requisitos

• Bachelor’s degree in computer science or equivalent experience • 10+ years of software engineering, solution architecture, enterprise architecture, cloud architecture, and/or AI architecture experience • 8+ years of experience designing and delivering cloud-native solutions using modern architecture patterns • Strong programming background, preferably with Python, and ability to guide architecture for Python-based AI services and applications • Hands-on experience architecting or building AI-enabled applications, GenAI solutions, AI agents, or AI platforms • Experience with AWS and/or Azure, including AWS Bedrock, AWS AgentCore, Azure AI Foundry, and Azure OpenAI • Strong understanding of GenAI architecture patterns, including LLM/SLM model selection, RAG, prompt engineering and evaluation, agentic workflows, tool/function calling, embeddings and vector search, human-in-the-loop systems, AI observability and monitoring, and model evaluation and quality benchmarking • Experience with agent frameworks and orchestration tools such as LangGraph, Semantic Kernel, or similar technologies • Experience with LLM ecosystems and providers such as OpenAI, Anthropic, Llama, Mistral, or similar model providers • Experience with vector databases and retrieval systems such as Pinecone, Azure AI Search, or equivalent technologies • Experience with tool, agent, and UI interoperability patterns, including AG-UI, A2A, MCP, registries, and reusable service layers • Experience integrating APIs, microservices, event-driven systems, and enterprise platforms into AI workflows • Strong understanding of microservices, APIs, event-driven systems, cloud services, serverless patterns, and platform-based architectures • Experience working in Agile/Scrum environments and partnering with product, engineering, operations, security, and compliance teams • Strong understanding of AI governance, responsible AI, privacy, compliance, and risk management considerations • Ability to translate business problems into scalable AI architecture, reusable solution patterns, and implementation roadmaps • Strong analytical, communication, decision-making, and problem-solving skills • Self-starter with the ability to lead through ambiguity, influence technical direction, and collaborate across teams

🏖️ Benefícios

• Annual performance-based bonus, commission, or other variable pay plan may be available • Medical benefits • Dental benefits • 401k • Fun, fast-paced environment with lots of room for growth