Principal Engineer

We are looking for a Principal Engineer to be the senior-most individual contributor at Hiver and own the technical vision, architecture, and AI engineering strategy across our product portfolio. You will work closely with the founders and CPO, influence engineering teams across the organisation, and play a hands-on role in defining how Hiver builds software at scale.

Responsibilities:

• Own the technical direction and architecture across Hiver's products and internal platforms.
• Drive long-term decisions around system design, data architecture, AI infrastructure, scalability, and engineering quality.
• Define technical standards across services, platforms, and engineering teams.
• Build internal AI platforms, evaluation systems, agentic development tools, code-generation pipelines, AI-assisted QA, retrieval and inference infrastructure.
• Drive the adoption of AI across engineering workflows and significantly improve engineering velocity.
• Stay at the forefront of AI-native product engineering and translate emerging technologies into practical, production-ready systems.
• Identify and prevent scalability, reliability, maintainability, and engineering-velocity challenges.
• Remain hands-on, writing code, building platforms, and validating ideas through working systems.
• Influence engineering leaders, product teams, and senior stakeholders across the organisation.
• Help shape Hiver's engineering culture and establish a high technical bar.

Requirements:

• 10+ years of software engineering experience, with a strong individual-contributor foundation.
• Extensive experience building scalable Cloud/SaaS products, enterprise infrastructure, or developer platforms.
• Strong expertise in distributed systems, system architecture, and production-scale software.
• Deep, hands-on understanding of AI/ML technologies, including foundation models, AI frameworks, embeddings, vector databases, LLMs, retrieval, inference, evaluations, and agentic systems.
• Proven experience shipping AI-powered products or building AI platforms in production.
• Strong understanding of both traditional distributed systems and the modern LLM/AI engineering stack.
• Experience making and owning large-scale architecture decisions in production environments.
• Ability to influence senior engineering and product leaders and drive alignment across complex organisations.
• Strong bias toward building and experimentation, rather than only reviewing designs or code.
• Track record of improving an engineering organisation's technical culture, practices, and velocity.
• Excellent communication skills, with the ability to simplify complex technical concepts for executive stakeholders.