Director - AI

The Director - AI is responsible for leading the design, development, and deployment of large‑scale, mission‑critical AI systems across Space
42’s geospatial, digital twin, and defense portfolios.

This role combines deep technical authority with end‑to‑end delivery leadership, overseeing the full AI lifecycle — from research and model development to production deployment, scaling, and operational governance.

The Director - AI leads high‑impact AI programs, ensures technical excellence across the AI stack, and guarantees that AI solutions meet national‑scale, sovereign, and defense‑grade requirements for performance, robustness, security, and explainability.

• Lead the architecture, development, and deployment of foundational and domain‑specific AI models, with a strong focus on geospatial AI, computer vision, predictive analytics, and decision‑support systems.
• Define and enforce AI system architectures that support large‑scale, secure, and high‑performance deployments across cloud, hybrid, and edge environments.
• Provide hands‑on technical guidance to senior engineers and AI specialists, ensuring best‑in‑class implementation, performance, and scalability.
• Drive adoption of modern AI frameworks, MLOps practices, and engineering standards.

• Own AI work streams across multiple concurrent commercial, government, and defense programs, ensuring delivery on time, on scope, and to quality standards.
• Translate operational, mission, and product requirements into executable AI roadmaps and delivery plans.
• Manage technical risks related to model performance, data quality, scalability, and operational constraints.
• Ensure smooth transition of AI solutions from research to production.

• Lead, mentor, and grow a team of AI engineers, ML researchers, and software engineers.
• Establish technical standards, coding practices, review processes, and quality gates.
• Build long‑term AI capability within the organization through coaching, mentoring, and knowledge sharing.
• Foster a culture of engineering rigor, accountability, and continuous improvement.

• Oversee implementation of robust MLOps pipelines covering training, testing, validation, deployment, monitoring, and retraining.
• Ensure models are production‑ready and operate reliably in high‑availability and constrained environments.
• Monitor model drift, performance degradation, and operational risks, implementing mitigation strategies.

• Work closely with Product Management, Platform Engineering, Security, and Operations teams.
• Act as a senior technical counterpart in discussions with executives, clients, partners, and government stakeholders.
• Contribute to technical solution designs, proposal development, and strategic bids where AI capabilities are a differentiator.
• Communicate progress, risks, and outcomes clearly to senior leadership.

• Master’s or PhD in Computer Science, Artificial Intelligence, Machine Learning, or a closely related field.
• Solid Linux and systems‑level expertise8+ years of experience in software engineering
• 8+ years of hands‑on experience in AI and ML development in production environments
• 5+ years designing and maintaining data warehouses or data lakes
• 5+ years designing, implementing, and maintaining custom ETL pipelines
• Proven experience deploying AI systems at scale
• Ability to read scientific literature and implement algorithms from scratch
• Strong mentoring skills and proven ability to lead senior technical teams

• Design and deployment of large‑scale AI systems and foundational models
• Advanced AI / ML frameworks (preferably PyTorch)
• Data…