Senior AI Engineer

Vaga não está no LinkedIn

🕒 Setembro 8

🔔 Pennsylvania, Virginia – Remoto

🔔 Pennsylvania – Remote ⚔️ Virginia – Remote

⏰ Tempo Integral

🟠 Sênior

🤖 Engenheiro de IA

👻 Score fantasma 14%

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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Air

SiteLinkedInTodas as Vagas

51 - 200 funcionários

Fundada em 2017

☁️ SaaS

📱 Mídia

📣 Marketing

💰 $35.000.000 Series B - Air em 2025-01

SaaS • Media • Marketing

A Air é uma plataforma de creative operations e digital asset management (DAM) nativa de AI, que ajuda equipes a organizar, encontrar, editar, aprovar e multiplicar ativos criativos em escala. Ela combina busca conversacional, auto-tagging/creative intelligence, design com AI e edição em massa (Canvas), revisões e aprovações, gestão de workflows e de marca, integrações e segurança empresarial para centralizar bibliotecas criativas e acelerar a produção de conteúdo em todos os canais. A Air atende equipes de marketing, mídia, agências, varejo/e-commerce e produto que buscam workflows criativos mais rápidos e uma análise de performance de ativos orientada por dados.

Descrição

• Design, build, and improve production agentic AI systems for complex real-world problems • Develop agent architectures for reasoning, planning, tool use, context management, memory, and multi-step task execution • Build secure tools and capabilities for agents to interact with data, APIs, code, and external systems • Develop model and inference infrastructure for commercial and open-weight language models • Evaluate models, inference techniques, and emerging AI capabilities for production use • Build automated evaluation frameworks, datasets, benchmarks, and methodologies for agentic workflows • Improve agent performance through prompt and context engineering, model selection, tool design, inference strategies, and architecture • Build scalable APIs, services, and infrastructure for agent execution and AI-powered product experiences • Design asynchronous and long-running agent workflow systems • Build safe execution infrastructure for agent-generated code and computational workloads • Improve observability using logging, metrics, distributed tracing, dashboards, and alerting • Investigate failures across models, agents, application code, and distributed infrastructure • Optimize systems for latency, throughput, reliability, and infrastructure cost • Translate AI research and emerging techniques into production improvements • Collaborate with product, platform, security, and domain teams to move AI capabilities from experimentation to production

🎯 Requisitos

• U.S. Citizenship is required • 5+ years of experience building production software, AI/ML systems, distributed systems, or similar technical systems • Deep experience designing, building, and operating production AI agents or agent platforms • Experience developing core agent infrastructure, including agent runtimes, tool execution, context management, memory, orchestration, or related platform capabilities • Strong understanding of state-of-the-art agent architectures and engineering tradeoffs for reliable, production-grade agentic systems • Experience designing agents that use tools, reason across multi-step tasks, interact with external systems, and operate over long-running or complex workflows • Experience building agent evaluation systems, including task-level evaluations, behavioral evaluations, regression testing, and production quality measurement • Strong understanding of modern LLM systems, including model inference, context engineering, structured outputs, tool calling, retrieval, model selection, and agent-performance techniques • Ability to evaluate emerging models, research, and agent techniques and translate them into production systems • Strong Python programming experience and production-quality software development • Experience designing scalable APIs, services, asynchronous systems, and event-driven architectures • Experience operating production services using Kubernetes and AWS, GCP, or Azure • Strong understanding of distributed systems, containers, service orchestration, networking, storage, and scalable architectures • Ability to debug complex failures across model behavior, agent execution, application code, and production infrastructure • Ability to move between research and engineering, prototype ideas, evaluate them rigorously, and productionize successful approaches • Comfortable working in a rapidly evolving field • Desired: current U.S. security clearance or ability to obtain one with sponsorship • Desired: startup or entrepreneurial environment experience • Desired: secure code execution environments or AI-agent sandboxes • Desired: multi-agent architectures, agent-to-agent communication, or distributed agent execution • Desired: fine-tuning, post-training, reinforcement learning, or synthetic data generation • Desired: AI observability, tracing, and debugging infrastructure • Desired: inference latency, throughput, GPU utilization, or model-serving cost optimization • Desired: AI security, adversarial testing, or securing agentic systems • Desired: government, defense, or mission-critical environment experience

🏖️ Benefícios

• Equal Opportunity Employer • Security clearance sponsorship available for qualified candidates who can obtain one