Senior AI Engineer
New
G
Grafana LabsB2B SaaS
This is a remote opportunity and we are looking for candidates from the U.S.Full-TimeSenior
Salary$154,445 - $185,334 per year
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Job Details
- Experience
- 8+ years of software engineering experience
- Required Skills
- Node.jsPythonGCPJavascriptBigQueryPrompt EngineeringLangChain
Requirements
- 8+ years of software engineering experience with depth in backend development or systems integration.
- 2+ years hands-on experience applying LLMs/AI to production workflows.
- Strong proficiency in Python and JavaScript/Node.js.
- Experience with Git-based workflows, code review practices, and testing discipline.
- Hands-on experience with LLM patterns including prompt engineering, RAG, function calling, and structured output parsing.
- Experience building and operating multi-agent systems at scale, including orchestration patterns and state management.
- Deep familiarity with Google Cloud Platform, BigQuery, and serverless/containerized services like Cloud Run.
- Understanding of LLM failure modes, confidence thresholds, fallback logic, and latency management.
- Proven ability to deliver end-to-end projects with minimal direction.
- Clear technical communication skills for both engineering and business stakeholders.
Responsibilities
- Own end-to-end development of multi-agent AI systems from architecture through deployment and operation.
- Build modular, composable agentic systems using orchestration frameworks like LangChain, CrewAI, or Anthropic MCP.
- Develop reusable agentic skills accessible across interfaces including Slack, dashboards, and CLIs.
- Implement observability, logging, prompt iteration, model evaluation, and cost management for AI workflows.
- Establish governance, access controls, and compliance standards for AI, including PII handling and human-in-the-loop paths.
- Build APIs, microservices, and MCP servers to connect LLMs with business platforms like BigQuery, CRMs, and Slack.
- Architect RAG data flows connecting LLMs to internal knowledge bases and real-time business context.
- Partner with cross-functional teams to identify automation bottlenecks and deploy solutions using tools like n8n or Workato.
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