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Senior AI Engineer – AI Platform

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Published
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6 Oct 2026Apply before
Opportunity details

About this role.

AI Summary

ClickUp is seeking a Senior AI Engineer to build and operate the backend AI platform powering production LLM capabilities across its workspace product. The role combines distributed backend engineering, AI infrastructure, MLOps, and hands-on application of LLMs to user-facing features. Responsibilities include model serving, provider routing, observability, automated evaluation, privacy controls, and cost and reliability optimization. The engineer will work closely with product, frontend, and data teams while influencing platform architecture and AI engineering practices. This is a senior, high-impact engineering role focused on scalable and secure AI systems.

Role DNA

A quick view of the complexity, pace, ownership and collaboration implied by the job description.

Job Complexity

5/5
EasyHard

Pace & Pressure

5/5
RelaxedFast-paced

Autonomy Level

5/5
GuidedFull ownership

Communication Load

4/5
IndependentCollaborative
AI insightThe position requires deep expertise across production LLM systems, cloud-native distributed infrastructure, MLOps, backend APIs, privacy, and security. Success depends on independently making high-stakes architectural tradeoffs involving reliability, model quality, latency, and cost.

Salary analysis

Estimated compensation compared with the broader US market for similar roles.

Estimated job medianHighly competitive
$225,000
US market range$180k–$270k
AI insightThe disclosed annual base compensation range is USD 200,000 to USD 250,000, with a midpoint of USD 225,000. For a US-based senior AI platform engineer with LLM infrastructure, distributed systems, and MLOps expertise, a competitive market base-salary range is approximately USD 180,000 to USD 270,000 annually; total compensation may differ based on equity and other incentives.

Core skills

Skills and capabilities most closely associated with this opportunity.

Sample interview questions
How would you design an LLM platform that supports multiple providers while maintaining reliability and cost control?

I would introduce a provider-agnostic gateway with standardized request and response schemas, capability metadata, and policy-based routing. The routing layer would consider model quality, latency, availability, data-handling requirements, and cost, with circuit breakers, retries, fallbacks, and rate-limit controls. I would also implement per-model telemetry, token accounting, evaluation datasets, and budgets so routing decisions can be continuously measured and adjusted.

What would you include in a production model-serving and observability strategy?

I would instrument end-to-end traces for requests, retrieval, tool calls, model responses, and downstream user actions. Key metrics would include latency, error rates, token consumption, cost, throughput, provider availability, quality-evaluation scores, and safety-policy violations. Monitoring should be paired with alerting, structured logging with sensitive-data redaction, version tracking, rollback capability, and regular offline and online evaluations.

How would you protect customer data when integrating external LLM providers?

I would first classify data and minimize what is sent to providers through redaction, anonymization, and least-privilege access controls. The platform should enforce tenant isolation, encryption in transit and at rest, retention policies, audit logs, and configurable provider policies based on data residency and contractual requirements. I would also conduct vendor security reviews and build clear controls for consent, deletion, and incident response.

Describe how you would evaluate whether a new model should replace an existing model in a user-facing feature.

I would define task-specific quality, safety, latency, and cost metrics before testing. I would run reproducible offline evaluations using representative and adversarial datasets, then validate results with shadow traffic or a controlled A/B experiment. A rollout would require measurable improvement against thresholds, monitoring for regressions, and a straightforward rollback path.

How do you approach scaling a backend AI service with unpredictable demand?

I would separate synchronous user paths from asynchronous workloads and use queues for noncritical or long-running tasks. Autoscaling should be based on workload signals such as queue depth, concurrency, latency, and provider limits, while caching, batching, request deduplication, and token limits reduce unnecessary load. Capacity planning, graceful degradation, and fallback behavior would ensure the product remains usable during spikes or provider failures.

This analysis is generated from the job description. Salary estimates, role characteristics and sample answers are guidance, not employer-provided facts.

At ClickUp, we’re building the future of work: the first truly converged AI workspace unifying tasks, docs, chat, calendar, and enterprise search, all supercharged by context-driven AI. We are an AI-native company. Every team member is expected to leverage AI daily, and we evaluate AI fluency as part of our hiring process. Join us and help redefine what’s possible. 🚀

Role Overview:

We are seeking a skilled and experienced Senior AI Engineer – AI Platform to join our ClickUp Engineering team. In this role, you will play a critical part in both building the core AI platform and directly applying large language models (LLMs) to deliver intelligent features across ClickUp. You will focus on backend systems that enable scalable, reliable, and secure AI-powered capabilities, while also working hands-on with LLMs to solve real user problems and drive product innovation.

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, 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.

#LI-REMOTE

#LI-AK2
#LI-CC1

Equal Opportunity Employer

ClickUp is an Equal Opportunity Employer, and qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, or national origin.

Privacy Notice

ClickUp collects and processes personal data in accordance with applicable data protection laws. You can find further details by viewing our Global Candidate Privacy Notice.

If you are a Philippine Job Applicant, please also see our Philippine Data Privacy Notice for further details.

Visa Sponsorship

Please note we are unable to sponsor or take over sponsorship of an employment visa for roles outside of engineering and product at this time. Sponsorship for engineering and product roles is not guaranteed, but is instead based on the business needs for that specific role at that time. Please reach out to the recruiter with any questions.

Fraud Alert

ClickUp Talent Acquisition will only initiate contact via an @clickup.com email or through our official careers portal on clickup.com. We will never request fees, payments, or sensitive personal information. Please disregard any offers received outside these channels and report them to support@clickup.com.

AI Processing Notice

ClickUp may use artificial intelligence and machine learning technologies to help review and screen candidates’ employment applications against role-related criteria. These tools support, but do not replace, human decision‑making. If you have questions or need an accommodation in the recruitment process, please contact us at AskPeople@ClickUp.com.

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