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Staff AI Engineer | US | Remote

4 weeks ago
United States
Full-time
Lead
AI Engineer
Software Development
Apache Airflow CI/CD GCP HubSpot JavaScript LLM Microservices Node.js Prefect Python React Salesforce Serverless
Apply Now
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 148

Description

  • 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 such as LangChain, CrewAI, Anthropic MCP, or similar tools.
  • Develop reusable agent capabilities that can be accessed across Slack, dashboards, internal apps, and CLI interfaces.
  • Implement observability and feedback loops for AI systems, 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 escalation paths.
  • Build MCP servers, APIs, CLIs, and microservices that connect AI models to business systems such as BigQuery, Slack, CRMs, email, calendars, and analytics tools.
  • Architect retrieval-augmented generation data flows that connect LLMs to internal knowledge bases, customer data, and real-time business context.
  • Build serverless or containerized services on GCP, including Cloud Functions and Cloud Run, that scale with usage and integrate with Grafana's cloud infrastructure.
  • Partner with RevOps, Demand Generation, Regional Marketing, and SDR teams to identify automation opportunities and deliver measurable business outcomes.
  • Design and deploy automated workflows using orchestration tools or custom platforms, with CI/CD, testing, and production reliability standards.
  • Create documentation, playbooks, and enablement materials so partner teams can operate automation solutions independently.

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, 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, 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, and Claude Code.
  • Clear technical communication skills, with the ability to explain complex systems to both engineers and business stakeholders.
  • Experience with vector databases or retrieval pipelines such as Pinecone, Weaviate, ChromaDB, Qdrant, or pgvector (bonus).
  • Familiarity with marketing or sales platforms such as Salesforce, Customer.io, HubSpot, Marketo, or Outreach (bonus).
  • Experience with frontend frameworks such as React or Slack Block Kit for user-facing AI interfaces (bonus).
  • Experience with observability tooling for AI systems such as LangSmith, Weights & Biases, or custom evaluation frameworks (bonus).
  • Experience with workflow orchestration platforms such as n8n, Temporal, Prefect, or Airflow (bonus).
  • Familiarity with Model Context Protocol (MCP) or similar standards for connecting AI systems to data sources (bonus).
  • Prior work automating marketing, sales, or customer success workflows in a B2B SaaS environment (bonus).
  • Active participation in open-source communities is preferred.

Benefits

  • Base compensation range of USD $174,986 to USD $209,983 in the United States.
  • All roles include Restricted Stock Units (RSUs).
  • 100% remote, global culture.
  • Global annual leave policy of 30 days per year.
  • 3 days of annual leave reserved for Grafana Shutdown Days.
  • In-person onboarding for new hires.
  • Career growth pathways and development opportunities.

Interested in this position?

Apply directly on the company website

Apply Now

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