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.

Requirements

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, or similar).
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.
Passion for staying at the forefront of AI infrastructure and applying new technologies to solve real-world problems at scale.

Benefits

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

AI platform servicesLLMsAPIsbackend systemsmodel servingmonitoringloggingautomated evaluationorchestration frameworksMLOps

Soft Skills

collaborationcommunicationcross-functional teamwork