Senior Applied AI Engineer

🕒 Agosto 14

🌐 Estados Unidos, Canadá – Remoto

🇺🇸 Estados Unidos – Remoto (EUA) 🇨🇦 Canadá – Remoto

💵 $160.000 - $190.000 / ano

⏰ Tempo Integral

🟠 Sênior

🤖 Engenheiro de IA

🦅 Patrocina Visto H1B

Esta empresa já patrocinou vistos H1B no passado.

👻 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.

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

Tango

SiteLinkedInTodas as Vagas

201 - 500 funcionários

🏗️ Construção

📦 Logística

💼 Consultoria

Construction • Logistics • Consulting

A Tango é uma empresa de software que fornece uma plataforma de inteligência conectada para gerenciamento de imóveis comerciais ao longo de todo o ciclo de vida da propriedade. Seus produtos SaaS incluem estratégia de portfólio, seleção de locais e análises preditivas, gestão de contratos de locação e transações, coordenação de projetos e manutenção, ferramentas de ocupação e locais de trabalho, e energia e sustentabilidade (utilitários, emissões e relatórios ESG). A Tango atende corporativos do setor imobiliário, varejistas, proprietários e clientes governamentais para otimizar o espaço, reduzir custos e alcançar metas de sustentabilidade.

Descrição

• Build and ship Tango’s first AI-powered product • Design, build, and ship production AI agents on LangGraph • Own agents end to end, including graph design, tool definitions, prompt and context engineering, durable execution, failure and retry behavior, and cost and latency budgets • Build agent tooling against internal systems over MCP, using direct API calls and agent-to-agent interfaces where appropriate • Deliver human-in-the-loop review flows with interrupt points, confidence surfacing, and correction paths • Build and tune retrieval, including chunking, hybrid retrieval, grounding, and citation to source page and paragraph • Contribute agent evaluations using golden datasets, LLM-as-judge and deterministic scorers, and CI regression suites • Diagnose quality failures and correct retrieval, prompt, tooling, model, or ground-truth issues • Own agent-level safety behavior, including prompt-injection resistance, PII handling, refusal, and escalation paths • Partner with Product to translate accuracy thresholds, confidence disclosure, and human-in-the-loop triggers into shipped behavior • Work with Platform Engineering on deployment and Data Platform on curated datasets • Feed agent session and usage analytics into the warehouse • Transition reference agents to domain teams and contribute to the shared agent quality standard

🎯 Requisitos

• 7+ years of professional software engineering experience • 2+ years building LLM-powered systems that reached production and real users • Strong expertise with Python and its service stack, including FastAPI, Pydantic, or equivalents • Experience with testing, code review, CI/CD, and production ownership • Production experience with an agent orchestration framework; LangGraph strongly preferred • Hands-on depth with at least one frontier model API • Hands-on experience with LLM evaluation, including golden datasets, LLM-as-judge, deterministic scorers, regression testing, and release gating • Experience with MCP tool servers or comparable tool and function-calling protocols • Experience with multi-agent patterns • Production RAG and retrieval experience, including chunking, hybrid retrieval, grounding, citation, and diagnosing retrieval failures • Experience with LLM observability and tracing, such as LangSmith, Langfuse, Arize, or equivalent • Experience with prompt and version management • Sound judgment regarding hallucination, prompt injection, and silent degradation • Preferred: graph-backed agent memory or knowledge graphs, such as Neo4j • Preferred: production vector and hybrid retrieval stores, such as pgvector, Pinecone, Weaviate, or Qdrant • Preferred: async task orchestration for long-running document pipelines, such as Celery/Redis or equivalent • Preferred: document intelligence and information extraction at scale, including OCR, layout-aware parsing, and structured extraction from long documents • Applicants must be authorized to work in the U.S. for any employer • Tango cannot sponsor employment-based visas at this time

🏖️ Benefícios

• Health, dental, and vision insurance • 401(k) plan with company match • Generous paid time off • Fully remote work environment • Inclusive and collaborative culture • Equal opportunity employment