- Company Name
- ClickUp
- Job Title
- Senior AI Engineer - AI Platform
- Job Description
-
Job title: Senior AI Engineer – AI Platform
Role Summary: Design and build a scalable, secure AI platform that deploys, orchestrates, and maintains large language models (LLMs) and other AI solutions, and apply LLMs directly to develop intelligent product features for a web‑based collaborative workspace.
Expectations: Deliver production‑grade AI services at enterprise scale; collaborate cross‑functionally with product, frontend, and data teams; continuously evaluate and integrate state‑of‑the‑art AI infrastructure; adhere to privacy, security, and compliance standards; optimize performance, cost, and reliability.
Key Responsibilities:
- Architect, design, and implement AI platform services for LLM deployment, orchestration, and lifecycle management.
- Build and maintain robust APIs and backend systems that expose AI functionality to core product features.
- Develop model‑serving, monitoring, logging, and automated evaluation pipelines for production reliability.
- Integrate with multiple LLM providers (OpenAI, Anthropic, Google, etc.), manage model selection, routing, and fallback strategies.
- Apply best practices for AI privacy, security, and regulatory compliance, including data anonymization and secure data handling.
- Optimize platform performance, scalability, and cost using cloud‑native and distributed systems technologies.
- Stay up‑to‑date with AI infrastructure, MLOps, and LLM advances; incorporate relevant innovations into the platform.
- Collaborate across engineering, product, and data teams to deliver seamless, user‑centric AI experiences.
Required Skills:
- Extensive background in designing and operating scalable AI/ML platforms in production.
- Proven experience applying LLMs to real‑world product features.
- Deep expertise in backend engineering, distributed systems, and cloud‑native tech (Kubernetes, Docker, AWS/GCP/Azure).
- Proficiency in orchestration frameworks/workflow engines (LangGraph, Airflow, Kubeflow, Ray, etc.).
- Strong programming skills in Python, Go, TypeScript, or similar backend languages.
- MLOps experience: model deployment, monitoring, logging, automated evaluation.
- Knowledge of AI privacy and security (data anonymization, compliance with data protection laws).
- Familiarity with search technologies and their integration into AI applications.
- Excellent collaboration and communication skills in cross‑functional environments.
- Passion for emerging AI infrastructure and solving large‑scale problems.
Required Education & Certifications:
- Bachelor’s (or higher) degree in Computer Science, Engineering, or related field; advanced degree preferred.
- Relevant certifications in cloud platforms (AWS Certified Solutions Architect, GCP Professional Cloud Architect, Azure Solutions Architect) and MLOps (e.g., MLOps Foundation) are a plus.