Director - AI

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 workstreams 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.

Stakeholder & Cross‑Functional Collaboration

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.

Design and deployment of large‑scale AI systems and foundational models

Advanced AI / ML frameworks (preferably PyTorch)

Data Warehouse / Data Lake architectures

Custom ETL design, implementation, and maintenance

MLOps, model lifecycle management, and production AI systems

Cloud platforms: AWS, Azure, GCP

Strong programming skills in Python and compiled languages (C++, Rust, Go, Java)

Performance profiling and optimization of AI systems

Applying a strong analytical and systems‑thinking perspective

Promoting integrity, ethics, and engineering rigor

Building collaborative, high‑performance teams

Communicating complex technical concepts clearly to technical and non‑technical stakeholders

Leadership under delivery pressure