Founding Engineer

We're looking for an exceptional Backend AI Infrastructure Engineer to join our founding engineering team. This role is ideal for engineers who enjoy solving complex infrastructure challenges, building scalable backend systems, and working at the cutting edge of AI. You'll work directly with the founders to architect and scale the core infrastructure powering our AI platform. From distributed systems and cloud compute optimisation to AI agents and data pipelines, you'll own mission-critical engineering problems and have a direct impact on the company's technical direction. If you love building systems from the ground up, thrive in ambiguity, and enjoy shipping quickly without compromising engineering quality, we'd love to meet you.

Responsibilities:

• Own and scale the backend infrastructure powering our AI data platform.
• Design, build, and optimise distributed systems, cloud infrastructure, and worker orchestration.
• Build robust data pipelines capable of processing large-scale datasets efficiently.
• Work on research-grade engineering challenges involving AI agents, LLMs, model harnesses, and emerging AI frameworks.
• Build internal developer tools and automation that improve data quality, operational efficiency, and engineering velocity.
• Collaborate closely with founders across Engineering, Product, and Operations to define priorities and execute high-impact initiatives.
• Translate real-world workflows into scalable agent training environments and AI-powered automation.
• Drive technical decisions, improve engineering practices, and raise the overall quality bar within the team.

Requirements:

• 4-7 years of software engineering experience in high-performance engineering teams.
• Experience at AI-first startups, deep-tech companies, or top product companies (FAANG or equivalent is a strong plus).
• Strong expertise in: Backend Engineering, Distributed Systems, Cloud Infrastructure (AWS/GCP/Azure), Scalable Microservices, Worker Orchestration & Job Scheduling, Performance Optimisation.
• Hands-on experience building or supporting AI/ML infrastructure, LLM platforms, AI agents, model serving, or post-training systems.
• Strong programming skills in Python, Go, Java, or Rust.
• Familiarity with modern AI tooling, LLM ecosystems, inference frameworks, and open-source AI technologies.
• Excellent problem-solving ability with a bias toward ownership and execution.
• Comfortable working in fast-paced, highly ambiguous startup environments with minimal supervision.