Staff AI Engineer

🕒 Abril 13

🇺🇸 Estados Unidos – Remoto (EUA)

💵 $174.986 - $209.983 / ano

⏰ Tempo Integral

🔴 Especialista

🤖 Engenheiro de IA

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Grafana Labs

SiteLinkedInTodas as Vagas

501 - 1000 funcionários

Fundada em 2014

🏢 Corporativo

☁️ SaaS

🤖 Inteligência Artificial

Enterprise • SaaS • Artificial Intelligence

Grafana Labs é uma empresa especializada em tecnologias e soluções de observabilidade open source. Ela oferece um conjunto abrangente de ferramentas para logs, métricas, tracing e gerenciamento de perfis (profiling), com produtos como Grafana, Loki, Tempo e Mimir. Seus recursos são projetados para ajudar empresas a visualizar, monitorar e gerar alertas a partir de dados de diversas fontes, oferecendo capacidades como detecção de anomalias, análise de causa raiz e gestão de SLOs (Service Level Objectives) com insights de IA/ML. A Grafana Labs disponibiliza soluções em nuvem e autogerenciadas, ideais para observabilidade de infraestrutura, aplicações e frontend. Além disso, sua plataforma suporta integração com diversas fontes de dados, como Prometheus e OpenTelemetry, tornando a empresa uma referência em observabilidade e monitoramento de infraestrutura.

Descrição

• Own end-to-end development of multi-agent AI systems, from architecture and implementation through testing, deployment, and ongoing operation • Build modular, composable agentic systems using orchestration frameworks (LangChain, CrewAI, Anthropic MCP, or similar) that operate 24/7 across teams • Develop reusable agentic skills that agents invoke across interfaces (Slack, dashboards, internal apps, CLIs) • Implement observability and feedback loops including logging, performance metrics, prompt iteration, model evaluation, and cost management • Establish governance and compliance standards for AI workflows including access controls, audit trails, PII handling, and human-in-the-loop escalation paths • Build MCP servers, APIs, CLIs, and microservices connecting AI models to business systems (BigQuery, Slack, CRMs, email, calendars, analytics tools) • Architect data flows for retrieval-augmented generation (RAG), connecting LLMs to internal knowledge bases, customer data, and real-time business context • Build serverless or containerized services (GCP Cloud Functions, Cloud Run) that scale with usage and integrate with Grafana's cloud infrastructure • Partner with RevOps, Demand Generation, Regional Marketing, and SDR teams to scope high-impact automation problems, identify bottlenecks, and build solutions with measurable business outcomes • Design and deploy workflows using orchestration tools (n8n, Workato, or custom platforms) with CI/CD, testing, and production reliability standards • Build systems designed for self-service with documentation, playbooks, and enablement materials that let partner teams operate independently

🎯 Requisitos

• 8+ years of software engineering experience with depth in backend development, systems integration, or data/analytics engineering • 2+ years hands-on experience applying LLMs/AI to production workflows, not just prototypes • Strong proficiency in Python and JavaScript/Node.js with Git-based workflows, code review practices, and testing discipline • Hands-on experience with LLM frameworks and patterns including prompt engineering, RAG, function calling/tool use, structured output parsing, and evaluation • Experience building and operating multi-agent systems at scale including agent decomposition, orchestration patterns (sequential chains, router/dispatcher, parallel fan-out), state management, and production monitoring • Diagnose business problems before writing code; think in workflows and outcomes, not just functions • Deep familiarity with Google Cloud Platform, BigQuery, and serverless/containerized services (Cloud Functions, Cloud Run) • Understanding of LLM failure modes and production mitigations including confidence thresholds, fallback logic, human escalation, and cost/latency management • Proven ability to identify high-leverage problems, push back on low-impact requests, and deliver end-to-end with minimal direction • Fluent with AI-assisted development tools (GitHub Copilot, Cursor, Claude Code); use AI to build AI systems • Clear technical communicator—able to explain complex systems in simple terms to both engineers and business stakeholders.

🏖️ Benefícios

• equity • bonus (if applicable) • Restricted Stock Units (RSUs) • 30 days annual leave