The Security Generative AI team is revolutionizing traditional security operations workflows with innovative features built on top of the Elastic Stack and the Elastic Search AI platform. The Elastic stack is already very popular among the security analyst community, and the Security Generative AI team has the opportunity to significantly improve the user experience and workflows of security analysts. We are using the power of the Elastic Search AI platform along with machine learning and retrieval augmented generation (RAG) techniques to enhance operational efficiency and reduce the time to respond to security threats

The team is diverse and distributed. You will be working remotely with people from Germany, Spain, United States, United Kingdom, and more. We meet via Zoom, brainstorm in Google docs, discuss in GitHub issues, and chat on Slack.

We are ideally looking for candidates that are based in Hungary, Greece, Spain, Poland, Romania and the UK. Sponsorship and relocation are not offered. 

Your future responsibilities: 

• Write, test and maintain high-quality, client-side and server-side TypeScript code.

• Collaborate with cross-functional teams to build new AI-powered workflows and integrate AI functionality into existing Security Solution features.

• Work closely with the product and design teams to define requirements and craft intuitive user workflows powered by generative AI that address security analytics use cases.

• Work on open-source, contribute to the Kibana codebase and issues, connect with the Elastic community via GitHub, Slack, and discussion forums.

• Work with our support team to help customers answer questions and resolve issues.

Required skills:

• Extensive experience developing reasonably complex, high-quality software over multiple years and maintaining it in production environments. Experience with large-scale systems is a plus.

• Experience with Typescript, React, and Node.js

• Proven track record of writing robust unit, integration, and E2E tests.

• Familiarity with developing LLM and Retrieval Augmented Generation (RAG) applications.

• Ability to translate prompt engineering techniques into code.

• Deep familiarity with the LangChain framework and its related concepts (i.e., chains, agents, and tools).

• Familiarity with LLM application evaluation tools such as LangSmith.

• Strong understanding of machine learning concepts and generative AI models (i.e., GPT, Gemini, Mistral, Claude, etc.).

• Exceptional problem-solving skills and the ability to think creatively to solve challenging problems with AI technologies.

• Experience with Elasticsearch is a plus

• Ability to work in a distributed team throughout the world.