Denpasar, Bali, Indonesia · On-site
<p>We're hiring a Lead AI Product Engineer to take technical and product ownership of the AI systems at the heart of Kulu. This is a hands-on, player-coach role: you will lead engineers, but we are not looking for a trad…
Skills: AI Systems, LLM, Agent Architecture, Prompt Engineering, Software Engineering
Denpasar, Bali, Indonesia • On-site
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You will lead the engineering team and own the technical and product direction of AI agent systems, ensuring high-quality user experiences. This involves hands-on coding, architectural decision-making, and performing root-cause analysis on agent failures.
Candidates must have exceptional software engineering fundamentals and significant experience building production applications with modern LLMs. Strong product judgment, leadership experience, and the ability to work in a high-performance, in-person environment are required.
We're hiring a Lead AI Product Engineer to take technical and product ownership of the AI systems at the heart of Kulu. This is a hands-on, player-coach role: you will lead engineers, but we are not looking for a traditional engineering manager who manages process and leaves technical decisions to the team. We want someone who understands the product deeply, develops strong opinions about how it should work, guides and reviews engineers directly, investigates failures, makes architectural decisions and - when it's the fastest way forward - opens the codebase and ships things themselves.
Our product is built around real-time AI agents interacting with users, so many of our hardest product decisions are also engineering decisions. A prompt change can be a production behaviour change. A race condition can cause an agent to act on information that was true two seconds ago but is now wrong. Deciding what belongs in deterministic code versus an LLM can fundamentally change reliability. We need someone who enjoys thinking deeply about those problems.
About Kulu
Kulu is a high-performance, high-bandwidth communication team. We run live daily standups, Slack constantly, and jump into huddles rather than letting long async threads develop. Product, engineering and commercial conversations overlap heavily. This suits people who enjoy working closely with highly engaged colleagues, talking through hard problems in real time, sharing unfinished work, and moving quickly as new information emerges. It's probably not the right environment if your ideal style is to receive a well-defined problem, disappear for the day, and communicate primarily through async updates. There will be focused individual work — but we optimize for the speed and quality of the team as a whole.
We are deliberately moving toward a more in-person culture in Bali, and this role will be a role model for it - over time taking substantial responsibility for building the team and creating a high-performance office culture where exceptional engineers want to work.
You will be the senior technical and product authority for the behaviour of our AI product - responsible not just for engineers shipping software, but for building the right system, in the right way, producing the right behaviour for users.
The North Star is simple: is the agent getting better over time? We expect the quality of the agent experience - judgement, reliability, helpfulness, consistency - to improve continuously with real users. If it stagnates or degrades, that's a failure of technical and product leadership regardless of activity underneath it. Work can be delegated; responsibility for the resulting agent experience is not. The role isn't measured by velocity, test coverage or process metrics - those are means to an end. The end is a measurably better AI product.
In your first months: develop a deep understanding of how our system behaves in production; establish clear ways to measure agent quality; become one of the people best able to explain why an agent behaved incorrectly; establish clear technical ownership; improve root-cause analysis; fix architectural weaknesses behind recurring failures; raise the quality of technical decision-making; personally solve some of our hardest AI product problems; and develop the engineers around you.
We care far more about evidence you can do these things than titles - you do not need to have been a Head of Engineering. We're particularly interested in founding engineers, senior/staff AI product engineers, technical founders, and technical leads in small, high-performing teams.
Nice to have (optional): Experience building voice/video agents or real-time conversational AI; strong Python or TypeScript skills; backend or full-stack experience; real-time media and streaming (e.g., LiveKit, Pipecat); speech pipelines (STT/TTS); LLM APIs (e.g., Gemini, OpenAI, Anthropic) and orchestration frameworks; evals and observability (e.g., Langfuse or equivalent); relational databases and vector/retrieval systems.
This is unlikely to be right if your model of leadership is primarily “hire great engineers, give them goals and get out of the way.” We're also unlikely to fit if you no longer want to write or closely inspect code, see product judgment as someone else's job, default to process and test coverage as the answer to quality problems, are uncomfortable challenging engineers' decisions, prefer managing through tickets and ceremonies, want a highly asynchronous low-communication environment, or have mainly worked in classical ML or model training without substantial application-layer AI experience.
We intentionally call this role Lead AI Product Engineer rather than Head of Engineering - we want someone who still identifies as a builder. For an exceptional person who can lead both the product and the team at increasing scale, there is a natural path toward Head of AI Product Engineering and broader technical leadership as Kulu grows.
AI onboarding infrastructure for B2B software companies
Kulu is a platform that enables software companies to launch screen-aware AI agents that run live customer onboarding calls. Customer success teams use these agents to give them 30% of their time back every week while scaling white-glove onboarding to every account. Kulu is led by a team of exited founders, AI PhDs and seasoned operators with backing from the likes of Antler, RedBus Ventures and Ultra VC - early backers of Lovable, Airalo, and Cleo.
Offices: London, Greater London EC2A 4NA, GB
AI onboarding infrastructure for B2B software companies
Kulu is a platform that enables software companies to launch screen-aware AI agents that run live customer onboarding calls. Customer success teams use these agents to give them 30% of their time back every week while scaling white-glove onboarding to every account. Kulu is led by a team of exited founders, AI PhDs and seasoned operators with backing from the likes of Antler, RedBus Ventures and Ultra VC - early backers of Lovable, Airalo, and Cleo.
Offices: London, Greater London EC2A 4NA, GB
