About the Role
A mission-driven, early-stage startup is looking for an AI Tech Lead to join its growing team.
This is a hands-on leadership role where you'll help shape a cutting-edge AI platform designed to drive real-world behaviour change and improve human performance and wellbeing.
The platform's first focus is on employee wellbeing in high-stress industries—and the mission is just getting started.
Key Responsibilities:
* Lead and mentor a senior engineering team working across backend, ML, and infrastructure.
* Play key role in design, development, and deployment AI applications using LLM's, Agentic framework, and other related technologies.
* Own technical direction for core systems, focusing on scalability, performance, and reliability.
* Write clean, maintainable code and contribute actively to the codebase.
* Define and uphold engineering best practices (code quality, CI/CD, observability, etc.).
* Collaborate closely with the CTO and product team to align technical delivery with strategic goals.
* Continuously improve team operations, development workflows, and developer experience.
* Play a key role in hiring and onboarding as the team grows.
Required Skills and Qualifications:
* 7+ years of commercial software engineering experience with a strong backend focus.
* Proven ability to lead engineering projects and/or teams.
* Experience with LangGraph, and a good understanding of agentic patterns (e.g. self-reflection, prompt/response-optimisation, multi-modal guardrails, cross-reflection, role-based cooperation).
* Hands-on experience in launching GenAI products, including agentic systems and multi-agent frameworks, driving real-world AI applications from concept to deployment.
* Experience in fast-paced or startup environments.
* BSc in Computer Science, Data Science, or related technical discipline.
* Strong communication skills and a bias toward action.
Technologies You'll Work With:
* Languages/Frameworks: Python, FastAPI, Pydantic, Streamlit (for internal tools)
* AI: AgenticFlows, GenAI, LLMs, and multimodal systems
* Architecture: Microservices, RESTful APIs, async programming
* Infrastructure: Docker, Terraform, GitHub Actions, GCP (preferred)
* Datastores: MongoDB, Redis
* Monitoring/Tooling: Prometheus, Grafana, Sentry
The role is remote with occasional travel.