Senior AI Engineer - AI Platform

Key Responsibilities

• Architect, design, and implement scalable AI platform services that support the deployment, orchestration, and lifecycle management of LLMs and other AI models.
• Apply LLMs and other AI technologies directly to build and enhance ClickUp’s intelligent features, working closely with product and engineering teams to deliver impactful solutions.
• Build and maintain robust APIs and backend systems that enable seamless integration of AI-powered features into ClickUp’s core platform.
• Develop infrastructure for model serving, monitoring, logging, and automated evaluation to ensure high reliability and performance of AI services in production.
• Integrate with multiple LLM providers (e.g., OpenAI, Anthropic, Google) and manage model selection, routing, and fallback strategies for optimal performance and cost.
• Drive the adoption of best practices in AI privacy, security, and compliance, including data anonymization, secure data handling, and regulatory adherence.
• Optimize platform performance, scalability, and cost-efficiency, leveraging cloud-native technologies and distributed systems.
• Stay current with advancements in AI infrastructure, MLOps, and LLM applications, and proactively incorporate relevant innovations into ClickUp’s AI platform.
• Collaborate cross-functionally with product, frontend, and data teams to deliver seamless, reliable, and user-centric AI experiences.

Qualifications

• Extensive experience designing and building scalable AI/ML platforms or infrastructure in a production environment.
• Proven track record of applying LLMs and AI models to real-world product features and user-facing solutions.
• Deep expertise in backend engineering, distributed systems, and cloud-native technologies (e.g., Kubernetes, Docker, AWS/GCP/Azure).
• Proven experience integrating and managing multiple LLMs and AI models, with a strong understanding of their operational requirements and limitations.
• Proficiency in orchestration frameworks and workflow engines (e.g., LangGraph, Airflow, Kubeflow, Ray).
• Strong programming skills in Python, Go, TypeScript or similar languages used for backend and AI platform development.
• Experience with MLOps best practices, including model deployment, monitoring, logging, and automated evaluation.
• Demonstrated ability to address AI privacy and security challenges, including data anonymization and compliance with data protection regulations.
• Familiarity with search technologies and their integration into AI-driven applications.
• Excellent collaboration and communication skills, with a track record of working effectively in cross-functional teams.