Sr Software Engineer, Cribl AI

Why You'll Love This Role

You will work closely with the founding team and a group of highly-skilled engineers to shape the future of search and analytics of observability data. You will play a central role in bringing integrating cutting-edge Generative AI technologies with the Cribl Product suite to help solve real customer problems. You will work closely with development partners and key stakeholders to iteratively design, develop, and deliver products and surfaces that will delight our customers. On top of it all you will have fun. Cribl strives to be a great place to work for everyone.

As An Active Member Of Our Team, You Will...

• Productionize, launch, and operate AI-based technology integrations into Cribl’s core products with the goal of solving real customer problems

• Partner with product & design leaders to prototype and experiment with new AI features

• Stay up-to-date with the latest AI technologies and trends

• This position will require stand-by, on-call, or off-hours duties

If You've Got It - We Want It

• 5+ years of professional software engineering experience building AI features end to end in production across product, backend, and model integration layers

• Proven fullstack experience, including designing and scaling React-based UIs and backend services or APIs, with strength in backend and systems thinking

• Deep expertise in TypeScript or JavaScript plus experience with at least one backend language or runtime such as Node.js, Go, Java, or similar

• Professional experience building AI agent-driven product experiences, including conversational interfaces, tool-calling patterns, RAG, prompt engineering, evaluation or guardrail techniques, and agent orchestration connected to reliable backend and data systems

• Professional experience with Model Context Protocols (MCPs), agent frameworks, orchestration layers, and integrating external tools and data sources into LLM-based systems

• Machine learning experience, ideally in applied settings where models or AI systems were shipped, integrated, evaluated, or operated in production

• Familiarity with data and infrastructure patterns for AI systems, including databases, APIs, observability, and integrating external tools, services, and data sources in production environments

• Ability to problem-solve from first principles, make sound engineering trade-offs aligned with product and business goals, and drive work independently through ambiguity

• Excellent communication skills, both verbal and written, with the ability to explain complex technical topics to cross-functional stakeholders in a remote or distributed environment

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