Senior Applied AI Engineer

- Design and launch LLM-powered assistant features such as conversational workflows, agent behaviors, retrieval pipelines, and multimodal interactions. - Construct prompt architectures, system instructions, and orchestration logic to guarantee reliability and personality consistency. - Rapidly prototype new functionalities and iterate based on user feedback and evaluation data. - Create and uphold evaluation frameworks for correctness, safety, grounding, and user experience quality. - Implement hillclimbing loops across prompts, models, and tool-use strategies to consistently enhance assistant performance. - Investigate failure modes, design mitigations, and implement systematic improvements across the system. - Develop internal tools for prompt experimentation, model comparison telemetry, and debugging automated evaluation pipelines. - Establish reusable frameworks that improve the overall AI organizations ability to deliver high-quality assistant features. - Seamlessly integrate LLMs with product surfaces, APIs, and backend systems. - Develop lightweight ML components such as ranking, classification, summarization, and personalization to improve assistant intelligence. - Collaborate with product managers, designers, and researchers to transform ambiguous concepts into refined user experiences. - Work with a startup mentality, promoting quick action, iterative processes, and comfort with uncertainty. - Collaborate closely with researchers, engineers, and product leaders in a dynamic AI team where ideas are implemented swiftly and impacts are immediate. - Foster a culture of experimentation, clarity, and high-quality execution throughout the team.