Head of Applied AI Products

Head Of Applied Ai Products

Viridien is seeking a Head of Applied AI Products to lead the design and realization of our AI-native product ecosystem. This role sits at the intersection of engineering, research, and product architecture, defining the technical direction for AI-powered solutions and translating emerging AI capabilities into scalable, production-grade products.

The role focuses on transforming unstructured geoscience domain data into structured knowledge systems and building AI-native tools that enable advanced data analysis and customizable workflows. The Head of Applied AI Products will shape the AI roadmap, define system architectures, and ensure the successful delivery of innovative AI-driven capabilities aligned with Viridien's strategic goals.

Key Responsibilities

• AI Product Architecture & Strategy
• Define and own the AI product architecture and technical product roadmap.
• Translate emerging AI capabilities into scalable product architectures and user experiences.
• Establish best practices for building reliable, observable, and debuggable LLM-powered systems.
• AI Data Pipelines & Systems
• Design and improve end-to-end AI pipelines.
• Develop document ingestion, layout analysis, and information extraction capabilities.
• Build entity resolution processes aligned with standardized domain databases.
• Implement table understanding and schema normalization into predefined data schemas.
• Advanced AI & Analytics
• Design and implement advanced analytics capabilities.
• Develop domain-specific machine learning models in collaboration with subject matter experts.
• Build enhanced RAG (Retrieval-Augmented Generation) systems and AI-assisted research tools.
• AI Applications & Platforms
• Lead the development of AI-native applications and tools.
• Implement tool-calling and orchestration frameworks for domain-specific software.
• Develop data analysis and integration systems.
• Implement human-in-the-loop validation and feedback mechanisms.
• Technical Leadership & Prototyping
• Prototype core systems to validate feasibility and guide implementation.
• Partner with engineering teams to review designs and ensure strong technical architecture.
• Drive the transition from experimental AI capabilities to scalable production systems.

What We Are Looking For

• Strong engineering background (ML engineering, MLOps engineer, or equivalent).
• Proven experience building complex systems from 0→1.
• Ability to independently write production-quality code and build functional prototypes.
• Practical experience with LLM application architectures (e.g., RAG, agents, workflows, tool calling).
• Solid understanding of data pipelines, system design, and service-oriented architectures.
• Product-minded: able to reason about user value, tradeoffs, and adoption—not only implementation.
• Comfortable operating in high-ambiguity, fast-evolving technical environments.