Product Experience Specialist @ AI Startup - Rp Job Bali-Denpasar area,Denpasar Bali Indonesia,IT/Tech

Position: Product Experience Specialist @ High Growth AI Startup - Rp 20m-30m/month
Location: Denpasar

Who are we?

Kulu is an AI startup, backed by some of the world’s leading investors including Antler (backers of Lovable and Airalo) and Redbus (backers of Cleo). We are building AI agents for software companies that run video calls with their users to get them onboarded. Imagine joining a Zoom call with an AI to help you get set up using a new piece of software - just share your screen and speak with the AI as it guides you through configuration.

Kulu is led by a rockstar founding team:
Ed (CEO) - 1st PM at Teya ($1b+ valuation in 2 years) and one previous exit. Rio (CTO) - PhD in AI, specialising in computer vision. Oscar (CCO) - Former Head of Sales at multiple VC-backed companies.

Kulu has two offices:
London - Commercial Office, and Bali - Product & Engineering Office. The founding team works from both locations.

Why this role exists

This role exists to own product quality and maintain exceptional standards across Kulu. This role will take a holistic view on quality. Yes you will be responsible for ensuring no bugs slip through to production however many important product issues are not strict bugs — they are moments where the experience feels confusing, unnatural, or misaligned with how real users behave in their tools and workflows.

This role will take ownership of all of these areas, ensuring our product is reliable, bug-free, intuitive and suitable for our customers.

This role will systematically test the product end-to-end, try to break it, surface experiential issues, and identify capability gaps where the product cannot adequately support real-world user behaviour.

This role is based in Bali, with a relocation package available, and will start as a contract role with a clear path to full-time based on impact.

Tasks

Manual & exploratory QA testing

Continuously and creatively test the product by actively imagining and simulating scenarios that could break it or degrade the user experience.

This includes testing across:

Core user flows
Edge cases and failure scenario
Long-running or unusual usage patterns (e.g. extended sessions, repeated interactions)
Different configurations, tools, environments, and devices (e.g. desktop vs mobile)

You are expected to:

Think adversarially about how real users might use the product in unexpected ways
Ask “what happens if…” questions and test those scenarios in practice
Push the product beyond happy paths to uncover hidden weaknesses
Actively try to break assumptions, not just verify expected behaviour
Test both before and after releases to identify unintended side effects and behavioural drift

Examples include (but are not limited to):

Staying in a live session for extended periods
Asking the AI to handle complex, ambiguous, or high-stakes tasks (e.g. data migration, table or cell-level reasoning)
Using the product in noisy, degraded, or imperfect conditions
Switching devices or contexts mid-flow

2. Regression & release testing

Validate new features and agent capabilities before they go live
Re-test existing functionality after changes to ensure nothing degrades
Verify that previously fixed issues do not reappear in new releases

3. Clear issue reporting

Document issues in a way that makes them easy to understand and act on, including:

Clear reproduction steps
Expected vs actual behaviour
Supporting evidence such as screenshots, videos, logs, or audio recordings where relevant

Categorise issues clearly, for example:

Bug
Regression
UX / product issue
AI behaviour issue

Work closely with engineering and product to ensure issues are well-understood, properly scoped, and actionable.

Additional responsibility: product & AI experience quality

Alongside traditional QA work, this role helps maintain a high bar for product clarity and human-like AI behaviour.

This includes:

Flagging UX issues that are confusing, unclear, or unintuitive (even if technically working)
Testing AI behaviour for: unnatural phrasing or tone, awkward timing or interruptions, and over- or under-explanation
Calling out moments where “this technically works, but a real human wouldn’t do this”

Additional responsibility: capability gap discovery

While testing the product across different tools, integrations, and real-world setups,…


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