Director of Engineering – AI Adoption

Veryon

Director of Engineering leading the strategy and development of AI initiatives for Veryon. Overseeing AI product integration and organizational AI adoption with a focus on aviation solutions.

Posted 5/1/2026full-timeRemote • 🇺🇸 United StatesLeadWebsite

About the role

Key responsibilities & impact

Define and execute a company-wide AI strategy aligned with Veryon’s business objectives
Partner with ELT and SLT to identify, prioritize, and roadmap AI initiatives across all departments
Partner with Security and Compliance teams to grow and ensure adherence of Veryon’s AI governance, best practices, and responsible AI usage
Drive organization-wide AI adoption, including training and change management initiatives
Identify and deliver measurable business value through AI-driven efficiencies and insights
Lead the integration of AI capabilities across Veryon’s product suite
Define and execute the roadmap for evolving products into agentic, decision-capable systems
Collaborate with Product and Engineering teams to prioritize and deliver AI-driven features
Ensure scalable & reliable deployment of AI/ML models in production environments
Evaluate and incorporate emerging AI technologies into the product strategy
Build, lead, and mentor high-performing AI/ML engineering teams
Drive cross-functional collaboration across all departments of Veryon including technology, product, sales, marketing, customer support, customer success, people operations and finance
Oversee the full lifecycle of AI solutions (design, development, deployment, optimization)
Establish KPIs to measure AI impact, adoption, and ROI
Manage partnerships with external vendors and AI technology providers
Build lasting relationships with large enterprise customers such as commercial aviation operators and OEMs
Apply aviation expertise to ensure AI solutions are operationally relevant and compliant
Identify opportunities to enhance maintenance, diagnostics, and operational performance
Align AI initiatives with aviation standards, safety, and regulatory requirements

Requirements

What you’ll need

Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or related field
Engineering leadership experience with a strong focus on AI/ML initiatives
Proven track record of implementing AI solutions across multiple business functions
Deep expertise in Generative AI, Natural Language Processing (NLP), and Machine Learning
Experience building and scaling AI-enabled products in production environments
Strong understanding of data platforms, architectures, and MLOps practices
Demonstrated ability to influence executive stakeholders and lead organizational change
Aviation industry experience or strong domain knowledge

Benefits

Comp & perks

Health insurance
Professional development opportunities

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

AI strategyAI governanceAI adoptionAI-driven efficienciesAI/ML modelsGenerative AINatural Language ProcessingMachine LearningMLOpsdata platforms

Soft Skills

leadershipcollaborationinfluencementoringchange managementcommunicationorganizational changerelationship buildingcross-functional collaborationstrategic thinking

Certifications

Bachelor’s degree in Computer ScienceMaster’s degree in Computer ScienceBachelor’s degree in EngineeringMaster’s degree in EngineeringBachelor’s degree in Data ScienceMaster’s degree in Data Science