AI Engineer

Role overview Design and build AI systems that can reason, plan, and work with both structured and unstructured data. You’ll contribute to autonomous agents and the supporting retrieval, data, and knowledge systems, collaborating with research, product, and platform colleagues to bring these capabilities into production.

Responsibilities - Implement agents that handle complex, multi-step tasks in practical domains. - Build data pipelines that prepare structured and unstructured sources for agent workflows. - Develop and maintain retrieval-augmented generation systems using vector search and document stores. - Build and maintain knowledge graphs and memory systems used by agents. - Contribute modular components for planning, tool use, and self-reflection. - Evaluate agent performance and robustness, and work with other teams to integrate improvements into production systems.

Requirements - At least three years of experience in AI, machine learning, or a related field. - Strong Python skills and a solid understanding of AI system architecture. - Experience building intelligent agents or multi-component AI systems. - Practical knowledge of retrieval-augmented generation and vector search. - Experience with knowledge graphs or similar semantic data structures. - Familiarity with data pipelines and API integrations, plus the ability to evaluate autonomous systems. - Strong problem-solving, communication, and collaboration skills.

Nice to have - Experience with multi-agent systems, distributed AI, symbolic reasoning, or hybrid AI. - Exposure to enterprise data, business workflows, or domain-specific AI applications. - Open-source contributions or published research in AI.

Benefits and work setup - Flexible remote or hybrid work. - Compensation, equity, and benefits are offered; specific details are not provided.