Software Architect

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Iris.ai is a pioneering AI‑first company on a mission to transform how humans discover and apply knowledge. For over a decade, we’ve built intelligent systems that empower researchers, engineers, and product teams to work faster and more precisely with scientific and technical data.

Our product suite – Neuralith, Axion, and RSpace – supports end‑to‑end AI development, from data orchestration and retrieval to LLM evaluation and deployment. At the core of our work are Retrieval‑Augmented Generation (RAG) pipelines, LLM Evaluation Frameworks, and intelligent AI Agents that bring context‑awareness, accuracy, and task‑level reasoning to applied AI.

Backed by the European Innovation Council (EIC) and trusted by leading R&D teams across industries, we turn advanced AI research into real‑world tools that help organizations solve high‑impact problems.

Opportunity

We are seeking a Lead Software Architect (AI Systems) to define, evolve, and steward the architecture that powers our AI platform and products. This is a senior technical leadership role for a deep technologist who thrives in end‑to‑end systems design, guides engineering strategy, and works hands‑on to turn ideas into scalable, reliable solutions. You will drive architectural vision, ensure coherence across services and teams, and provide technical mentorship while collaborating closely with product managers and researchers.

What You’ll Do

• Architect end‑to‑end AI‑driven software systems with scalability, observability, and robustness at their core.
• Participate in the design of the technical roadmap and drive long‑term architectural evolution of our AI platform.
• Define system boundaries, service interfaces, data flows, storage strategies, and integration patterns.
• Evaluate and adopt new technologies to improve performance, developer productivity, and system reliability.
• Mentor engineers, set coding and design standards, and review critical system components.
• Ensure alignment between architecture, product strategy, and organizational goals.
• Guide technical planning, capacity management, and system‑level issue resolution.
• Participate in hiring, onboarding, and technical evaluation of engineering talent.

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