Director of AI and ML Engineering - Systems Integrator

Looking for a role with plenty of growth opportunities?

Join a leading IT solutions provider delivering security, cloud, networking, data center, and managed services to organizations worldwide. With a customer-first approach and deep technical expertise, the organization helps businesses modernize, optimize, and scale their IT infrastructure.

This opportunity is for a Director of AI & ML Engineering to lead the development, delivery, and operationalization of AI and machine learning capabilities across software products and internal platforms. The role involves building and mentoring an AI/ML engineering team, collaborating with cross‑functional stakeholders, and driving AI initiatives from strategy and deployment through ongoing governance, optimization, and lifecycle management.

Ready to make a move? Get in touch and apply today!

• Execute the company’s AI strategy, aligning with Customer’s business objectives and the evolving needs of the satellite connectivity industry
• Lead the design, build, and deployment of AI/ML solutions that improve customer experience and operational outcomes, including areas such as network/service insights, predictive maintenance, anomaly detection, support automation, and sales enablement
• Own the end-to-end delivery lifecycle for AI/ML initiatives: problem framing, data readiness, experimentation, production-ization, monitoring, and continuous improvement
• Partner with Product to translate business goals into actionable AI/ML roadmaps and measurable outcomes tied to customer and operational value
• Establish and mature ML Ops and LLM Ops practices: model versioning, CI/CD, evaluation, monitoring, drift detection, retraining workflows, and production support
• Define engineering standards for AI/ML systems including quality, reliability, security, latency, cost-to-serve, and scalability

• Demonstrated success taking AI/ML systems into production and owning operational performance (monitoring, reliability, retraining, cost)
• Strong experience with modern ML tooling and frameworks (e.g., PyTorch, Tensor Flow) and cloud‑based AI services (Azure, AWS, or GCP)
• Proven ability to lead cross‑functional execution and communicate effectively with engineering, product, and business stakeholders
• Strong understanding of data privacy, security, and governance practices in production systems
• Experience delivering AI/ML capabilities in connectivity, telecommunications, aviation, or other high‑reliability industries

• $220,000