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Staff AI Engineer | US | Remote

1 hour, 59 minutes ago
United States
Full-time
Lead
AI Engineer
Software Development
CI/CD CRM GCP Git Grafana HubSpot JavaScript Microservices Node.js Prefect Python React Salesforce
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Grafana

Grafana

Grafana is the open observability platform providing analytics, monitoring, and visualization solutions with a focus on user control and cost efficiency.

IT Services
1K-5K
Founded 2014
$535M raised
View All Jobs 95

Description

  • Own end-to-end development of multi-agent AI systems from architecture and implementation through testing, deployment, and ongoing operation.
  • Build modular agentic systems using orchestration frameworks such as LangChain, CrewAI, Anthropic MCP, or similar tools.
  • Develop reusable agent skills that can be accessed across Slack, dashboards, internal apps, and CLIs.
  • Implement observability and feedback loops for 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.
  • Build MCP servers, APIs, CLIs, and microservices that connect AI models to systems like BigQuery, Slack, CRMs, email, calendars, and analytics tools.
  • Architect retrieval-augmented generation data flows connecting LLMs to internal knowledge bases, customer data, and real-time business context.
  • Build serverless or containerized services on GCP, such as Cloud Functions and Cloud Run, that scale with usage.
  • Partner with RevOps, Demand Generation, Regional Marketing, and SDR teams to identify automation opportunities and deliver measurable outcomes.
  • Design and deploy reliable workflows using orchestration tools such as n8n, Workato, or custom platforms, with CI/CD, testing, and production standards.
  • Create documentation, playbooks, and enablement materials so partner teams can use automation systems independently.
  • Define technical direction for the automation platform, including data models, API contracts, shared libraries, and reference architectures.

Requirements

  • 8+ years of software engineering experience with depth in backend development, systems integration, or data/analytics engineering.
  • 2+ years of hands-on experience applying LLMs or 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 such as 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, state management, and production monitoring.
  • Deep familiarity with Google Cloud Platform, BigQuery, and serverless/containerized services such as Cloud Functions and 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.
  • Fluency with AI-assisted development tools such as GitHub Copilot, Cursor, or Claude Code.
  • Clear technical communication skills, with the ability to explain complex systems to engineers and business stakeholders.
  • Experience with frontend frameworks and tooling such as React, Slack Block Kit, or dashboard components is a plus.
  • Familiarity with GTM platforms such as Salesforce, HubSpot, Outreach, Gainsight, or similar CRM/sales engagement tools is a plus.
  • Experience with vector databases or retrieval pipelines such as Pinecone, Weaviate, ChromaDB, or pgvector is a plus.
  • Prior work automating sales, customer success, or marketing workflows in a B2B SaaS environment is a plus.
  • Experience with workflow automation platforms such as n8n, Prefect, Clay, PhantomBuster, Apify, or Dust is a plus.
  • Familiarity with Model Context Protocol (MCP) or similar standards for connecting AI systems to data sources and tools is a plus.
  • Exposure to observability tools for AI systems such as LangSmith, Weights & Biases, or custom logging and evaluation frameworks is a plus.
  • Experience working in Revenue Operations, GTM Analytics, or Sales Operations environments is a plus.
  • Previous experience in open source or developer-focused SaaS companies is a plus.
  • This is a remote role open to applicants in USA time zones only.

Benefits

  • Base salary range of USD 174,986 to USD 209,983 in the United States.
  • Equity as part of the compensation package.
  • Bonus eligibility, if applicable.
  • Restricted Stock Units (RSUs) for all employees.
  • 100% remote work with a global culture.
  • 30 days of annual leave per year, including 3 Grafana Shutdown Days.
  • In-person onboarding to help new hires ramp successfully.

Interested in this position?

Apply directly on the company website

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