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Senior AI Engineer – AI Product

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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 ship scalable, user-facing AI product capabilities for its converged productivity workspace. The role centers on integrating and orchestrating LLMs, developing evaluation frameworks, and improving AI features through experimentation, data, and user feedback. The engineer will partner closely with product, design, and engineering while addressing production reliability, observability, privacy, security, and compliance. Candidates need substantial backend or full-stack experience, including Python or JavaScript/TypeScript, relational databases, Elasticsearch, and a record of influencing technical and product direction.

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

5/5
IndependentCollaborative
AI insightThis is a senior, product-facing AI engineering role requiring production LLM expertise, multi-model orchestration, robust evaluation, and scalable systems design. Success requires independent technical leadership and the ability to turn ambiguous user and product needs into reliable AI experiences.

Salary analysis

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

Estimated job medianMarket rate
$225,000
US market range$190k–$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 senior US-based AI product engineer with production LLM and full-stack/backend expertise, an estimated competitive market base-salary range is approximately USD 190,000 to USD 270,000 annually; total compensation may differ based on equity, bonus, and location.

Core skills

Skills and capabilities most closely associated with this opportunity.

Sample interview questions
Describe an AI-powered product feature you shipped to production and how you measured its success.

I would explain the user problem, model and system architecture, safeguards, rollout plan, and measurable outcomes such as adoption, task completion, quality scores, latency, cost, and user feedback. I would also describe iterations made after observing production behavior.

How would you design a context-aware LLM feature for a productivity workspace?

I would start with a narrowly defined user workflow and establish data permissions and privacy boundaries. I would use retrieval and structured context assembly, select models based on quality, latency, and cost, add tool-use or orchestration where appropriate, and build evaluation datasets that reflect real user tasks before a staged release.

What approach would you take to evaluate the quality of an LLM-driven feature?

I would combine offline and online evaluation. Offline, I would create representative, versioned test sets with automated and human-reviewed quality criteria; online, I would monitor user acceptance, corrections, completion rates, safety signals, latency, and cost, then use controlled experiments to validate product impact.

How do you make AI features reliable and observable in production?

I would instrument the complete request path with structured logs, traces, model and prompt versions, retrieval metadata, latency, token usage, error categories, and quality outcomes. I would also implement fallbacks, rate limits, retries where safe, feature flags, monitoring alerts, and incident playbooks.

How would you address privacy and security when integrating multiple AI models?

I would apply least-privilege access, tenant isolation, data minimization, encryption, retention controls, vendor review, and clear audit logging. I would prevent unauthorized context retrieval, redact sensitive information where appropriate, validate tool permissions, and ensure model usage aligns with applicable compliance and user-consent requirements.

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 innovative Senior AI Engineer – AI Product to join our ClickUp Engineering team. In this role, you will drive the development of intelligent, user-facing features that leverage the latest advancements in AI and large language models (LLMs). You will work closely with product, design, and engineering teams to deliver seamless, impactful AI-powered experiences that delight our users and differentiate ClickUp in the productivity space. This is a product-focused engineering role requiring deep expertise in AI, LLMs, and building scalable, production-ready applications.

Key Responsibilities:

  • Lead the design, development, and deployment of AI-powered features and products that directly impact ClickUp users.

  • Collaborate with product managers, designers, and engineers to identify opportunities for AI-driven innovation and translate user needs into technical solutions.

  • Integrate and orchestrate multiple LLMs and AI models to deliver robust, context-aware, and personalized user experiences.

  • Prototype, test, and iterate on new AI features, leveraging user feedback and data to drive continuous improvement.

  • Ensure the reliability, scalability, and performance of AI-powered features in production environments.

  • Stay at the forefront of AI research and product trends, incorporating the latest advancements into ClickUp’s product roadmap.

  • Address AI privacy, security, and compliance challenges, ensuring responsible and ethical use of AI in user-facing applications.

  • Mentor and guide other engineers in best practices for building AI-powered products.

Qualifications:

  • Proven experience building and shipping AI-powered features or products in a production environment.

  • Deep understanding of LLMs and AI models, including their strengths, limitations, and integration strategies.

  • Experience working with orchestration frameworks and integrating multiple AI models to deliver cohesive user experiences.

  • Experience developing evaluation frameworks and metrics for AI features, with a focus on user impact and business value.

  • Familiarity with AI privacy, security, and compliance best practices.

  • 5+ years of backend and/or full-stack engineering experience, with proficiency in Python, JavaScript/TypeScript, or similar languages.

  • 5+ years of experience with PostgresDB, MySQL, or other related DBs.

  • 5+ years of experience with Elasticsearch or other related technologies.

  • Experience setting up production-ready observability and logging.

  • Demonstrated ability to collaborate cross-functionally and translate product requirements into technical solutions.

  • Passion for staying updated with the latest AI research and applying it to solve real-world user problems.

  • Excellent communication and mentorship skills, with a track record of influencing product direction and engineering best practices.

#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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