Director of AI Engineering

About the role

MRI Software is looking for a Director of AI Engineering to lead the architecture, delivery, and operation of AI capabilities across its platform and product portfolio. This senior technical leadership position owns the shared AI platform, drives AI‑native engineering practices, and builds the engineering organization that powers AI at scale.

Key responsibilities

• Define and execute MRI’s AI engineering roadmap, including build‑vs‑buy decisions and technology direction.
• Lead and scale the AI engineering organization responsible for model integration, RAG systems, agent orchestration, and AI platform services.
• Own the shared AI platform – prompt management, evaluation frameworks, vector databases, model gateway, routing services, and agent registries.
• Champion emerging interoperability standards such as Model Context Protocol to connect AI capabilities across the product ecosystem.
• Architect enterprise‑wide agent ecosystems, including interoperability, shared memory, and cross‑product orchestration.
• Establish reference architectures and reusable patterns to reduce product‑level fragmentation.
• Partner with product, IT, data, and security leaders to translate AI roadmap priorities into engineering execution.
• Implement AI‑assisted development tools, AIOps/LLMOps practices, observability, telemetry, and hallucination detection.

Required profile

• Proven technical leadership experience building and scaling AI platforms.
• Strong background in AI architecture, model lifecycle management, and large‑scale engineering organization design.
• Ability to collaborate with product, data, security, and executive stakeholders.
• Experience driving adoption of AI‑native engineering practices across multiple business units.

Required skills

• AI platform architecture
• Model integration and evaluation frameworks
• Retrieval‑augmented generation (RAG) systems
• Agent orchestration and enterprise agent ecosystems
• Vector databases and prompt management
• Model Context Protocol and AI interoperability standards
• AIOps / LLMOps practices including observability and telemetry
• AI‑assisted coding and workflow tooling