Our client is building a fully AI-powered workplace coaching platform that’s redefining how teams interact, learn, and perform - shaping the next frontier in human–AI collaboration. Powered by cutting-edge research in generative AI, multimodal reasoning, and behavioural simulation, their platform introduces synthetic AI personas that listen, adapt, and challenge in real time. These AI-driven simulations foster deeper learning, stronger leadership, and sharper decision-making across entire organisations.
Following a successful pre-seed round in 2025, the company is on track to reach profitability by Q1 2026.
Role Overview:
As a Chief Technology Officer and late Co-founder, you’ll be at the core of building an AI-native product - shaping systems where user input, AI reasoning, behavioural logic, and response generation happen in milliseconds.
Key Responsibilities
- Shape technical direction and engineering standards for a high‑growth team tackling some of the hardest problems in AI productisation.
- Design and build end‑to‑end features across the stack (JavaScript / Python), with a focus on integrating real-time, multi-turn AI dialogue into the user experience.
- Work closely with AI researchers to productionise LLM‑powered agents, including retrieval‑augmented memory, contextual feedback loops, and behavioural modelling.
- Develop core infrastructure to support latency-sensitive interaction - combining frontend responsiveness with backend reasoning pipelines.
- Build robust systems to manage prompt orchestration, token efficiency, streaming inference, and multi-agent coordination.
Qualifications:
- Strong entrepreneurial background, either as a founder or through hands-on experience working in a very early-stage (pre-seed) startup.
- A product-minded builder - comfortable navigating early-stage ambiguity and contributing across the full stack.
- Strong professional experience and a willingness to be hands-on with engineering, particularly using Python, TypeScript and React.
- Comfortable designing and consuming REST APIs and webhooks for real-time system communication.
- Confident working with Docker for local development and containerisation.
- Familiarity with AI-enhanced developer tooling such as Cursor, Claude Code, GitHub Copilot, or similar tools.
- Fluency in English.
If you’re excited by the challenge of turning raw LLM outputs into structured, emotionally intelligent experiences - and want to engineer AI products that go beyond novelty to actually improve how people think, act, and lead - we’d love to hear from you.