Sr Software Engineer, Cribl AI
Cribl · United States · 1mo ago
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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