Senior Software Engineer, AI Developer Tools

🕒 Outubro 14

🏄 California, Washington – Remoto

🏄 California – Remote ☕ Washington – Remote

💵 $160.900 - $260.700 / ano

⏰ Tempo Integral

🟠 Sênior

🤖 Engenheiro de IA

👻 Score fantasma 1%

O que significa: a chance de ninguém estar realmente contratando para esta vaga.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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Docker, Inc

SiteLinkedInTodas as Vagas

51 - 200 funcionários

💼 Consultoria

☁️ SaaS

💰 $105.000.000 Series C em 2022-03

Consulting • SaaS

Na Docker, simplificamos a vida dos desenvolvedores que estão criando aplicativos que mudam o mundo. A Docker ajuda os desenvolvedores a transformarem suas ideias em realidade, conquistando a complexidade do desenvolvimento de aplicativos. Simplificamos e aceleramos fluxos de trabalho com um pipeline de desenvolvimento integrado e componentes de aplicativos. Ativamente utilizado por milhões de desenvolvedores ao redor do mundo, o Docker Desktop e o Docker Hub oferecem simplicidade, agilidade e escolha incomparáveis.

Descrição

• Design, build, and operate production AI agents for developer productivity, including code review assistants, test generators, deployment diagnostics, and incident response automation • Integrate LLM providers, agent orchestration frameworks, and MCP servers into reliable tools • Build systems that help Docker engineers adopt AI-native development tools • Build integrations between AI developer tools and CI/CD pipelines, observability platforms, and deployment systems • Instrument tools to measure adoption, effectiveness, and developer satisfaction • Build and improve self-service platform capabilities including ArgoCD/GitOps deployment pipelines, Grafana observability integration, security controls, and cost management • Reduce time-to-production for new products from weeks to days • Contribute to reliability, security, and performance standards for AI systems, including SLOs, monitoring, and incident response • Take features and services from requirements through production • Write design documents and participate in design reviews • Review code and share knowledge with the team • Participate in the on-call rotation and improve alerts, runbooks, and tooling • Follow AI-assisted engineering practices and validate AI-generated output • Collaborate with Infrastructure, Security, Data, product engineering, and platform teams • Help newer engineers learn the team's tools, patterns, and practices • Track emerging AI/LLM technologies and agent frameworks and share useful findings

🎯 Requisitos

• 6+ years of software engineering experience building and operating production systems • Hands-on experience building LLM-powered applications, AI agents, or AI-assisted developer tools • Working knowledge of LLM APIs including OpenAI and Anthropic • Knowledge of prompt engineering, agent orchestration frameworks, and practical AI applications in software development workflows • Experience building and operating scalable backend services, distributed systems, or developer-facing platforms • Experience with cloud-native infrastructure, Kubernetes, CI/CD pipelines, and observability systems • Proficiency in Go, Rust, Java, or Python; Go preferred • Strong software engineering fundamentals • Experience building developer tools, platform systems, or internal tools used by other engineers • Good product judgment and ability to evaluate developer experience and technical trade-offs • Clear written and spoken communication suited to a remote, async-first company • Ownership mentality and bias for action and iterative delivery in ambiguous, fast-moving environments • Comfortable working autonomously in a distributed, remote-first team • Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience • Experience with MCP or similar AI agent integration standards preferred • Background in developer productivity, DevOps, SRE, or platform engineering preferred • Contributions to open source AI tools, developer tooling, or platform engineering projects preferred • Experience with GitOps deployment patterns such as ArgoCD or Grafana-based observability preferred • Familiarity with security and operational practices for production AI systems preferred • Experience with infrastructure-as-code such as Terraform or Pulumi and major cloud platforms such as AWS, GCP, or Azure preferred • Must be legally authorized to work in the United States

🏖️ Benefícios

• Equity for all full-time employees • Remote-first work from home • Flexible scheduling • Generous PTO • Quarterly Whaleness Days • End-of-year Whaleness break • Home office support • Technology stipend equivalent to US$100 net per month • Annual learning and development stipend for conferences, courses, certifications, and continued learning • 16 weeks of paid parental leave after six months of employment • Medical benefits • Retirement benefits • Paid holidays • Docker swag

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