Principal Engineer

Architecture and technical standards. You will set architecture direction across the entire product portfolio and internal platforms. You will own the long-horizon decisions on system design, data architecture, AI infrastructure, and engineering quality. You will be the technical conscience of R& D, the person who can see two product cycles ahead and pull decisions back to today.

AI-native product building. You will drive Hiver's transformation into an AI-native engineering organisation. This is not a side project. We believe the companies that win the next decade will be the ones whose engineering orgs absorb AI into how they build, not just what they ship. You will build the internal AI platforms, dev tooling, and engineering practices that make Hiver's product development 10x more AI-leveraged than it is today. You own that mandate end-to-end: platforms, workflows, culture, proof points. You will report to the founders and work closely with the CPO. You will influence every team at Hiver. This is a leadership role.

Responsibilities:

• Set technical direction for both products.
• Make the architecture calls others will live with for years.
• Set technical standards across services, platforms, and engineering teams.
• Raise the bar on system design, code quality, AI integration, and engineering velocity.
• Conceptualise and build internal AI platforms, eval management, agentic dev tooling, codegen pipelines, AI-assisted QA, retrieval and inference infrastructure. Change the unit economics of building software at Hiver.
• Operate at the bleeding edge of AI-native product engineering. Stay ahead of what's possible. Bring it back in code and in how we build.
• Prevent the predictable failure modes of a scaling product org: unmaintainable systems, reliability decay, manual-QA bloat, slow integration of AI primitives into the product.
• Stay hands-on. The people best positioned to challenge how we build are the ones still building.

Requirements:

• 12-14 years of engineering experience, anchored in a strong IC foundation. Most of your time today goes into architecture, technical direction, and platform building, but you still code when it sharpens a decision or proves a hypothesis.
• Cloud and platform expertise: 10+ years building scalable Cloud/SaaS products, enterprise infrastructure software, or developer platforms.
• Technical depth in AI. Deep, current understanding of the AI landscape. Hands-on fluency with AI frameworks, foundation models, embeddings, and vector databases. You have shipped AI features, built AI platforms, and have opinions on what works and what does not in the real world.
• Proven ability to influence engineering leaders, product teams, and stakeholders to achieve outcomes in complex environments.
• Acts as a force multiplier leveraging technical credibility to drive alignment and to overcome organisational barriers & friction points.
• Demonstrated ownership of large-scale architecture decisions in production.
• SaaS environment preferred.
• Fluency in both halves of the modern stack: classical distributed systems, and the new stack of LLMs, evals, agentic systems, retrieval, and inference economics.
• A bias for building over reviewing. You write code, ship tools, and prove ideas with working systems.
• Track record of moving an engineering team's technical culture, not just its output.
• Ability to communicate complex technical ideas in simple terms to the executive team.

Skills

AI, architecture, cloud, Distributed Systems, embeddings, platforms, SaaS, vector databases