AI Engineer

Role overview Build production AI applications such as conversational agents, knowledge assistants and automated workflows. The role spans model integration, backend engineering and evaluation, with a focus on making features reliable, secure, responsive and useful beyond an initial prototype.

Responsibilities - Develop and ship AI features, including conversational and voice experiences and workflow automation. - Connect agents to business APIs and tools with appropriate permissions, validation and human handoffs. - Build retrieval pipelines for document ingestion, search and responses grounded in source material. - Design prompts, conversation flows and realistic evaluations for task completion, accuracy and failure handling. - Measure and improve latency, streaming, reliability and operating cost through controlled experiments. - Add logging, tests and safeguards for sensitive data, prompt injection and unintended tool use. - Work with product, design and engineering colleagues to turn prototypes into maintainable services.

Requirements - Practical experience developing applications with large language models and external APIs. - Strong Python or TypeScript skills and experience building backend services. - Understanding of tool calling, structured outputs, retrieval-augmented generation and embeddings. - Experience evaluating model responses with realistic cases and investigating inconsistent results. - Working knowledge of databases, authentication, Git, automated testing and deployment. - Ability to explain engineering trade-offs and collaborate clearly in a remote team.

Nice to have - Experience with real-time voice, speech technology or multilingual agents. - Relevant project examples or a code portfolio to share.

Benefits and work setup - Fully remote, with applicants considered worldwide.