Director of AI Engineering

Responsibilities:

• Hire, mentor, and develop a team of AI and full-stack engineers. Set performance expectations, run career development conversations, and build a culture of craft, collaboration, and psychological safety. Define org structure and hiring roadmap as the function scales.
• Own the multi-year vision for AI adoption across engineering. Define standards, patterns, and best practices for genAI, embeddings, RAG, agent workflows, and intelligent automation. Partner with architecture, product, and business leadership to align AI strategy with enterprise goals.
• Lead the strategy and delivery of AI capabilities embedded in mobile applications, across iOS, Android, and cross-platform frameworks. Partner with product and design to identify where on-device intelligence, conversational interfaces, and AI-assisted workflows create genuine value for mobile users. Establish mobile-specific patterns for model integration, latency management, offline-capable inference, and responsible data handling, ensuring AI features meet enterprise security and performance standards on the device.
• Establish model governance frameworks, scalable lifecycle practices, and responsible AI standards across the organization. Ensure AI initiatives are secure, compliant, and aligned with enterprise architecture guidelines and SLA commitments.
• Serve as the primary AI engineering voice in executive and cross-functional conversations. Translate technical complexity into business impact, influence product roadmaps, and build trust across engineering, architecture, and business leadership.
• Review and guide end-to-end solution design across UI, APIs, microservices, middleware, and data pipelines. Provide technical direction on high-stakes decisions, evaluate build vs. buy tradeoffs, and ensure your team delivers stable, reusable, production-quality AI solutions.

Requirements:

• 10 years of software engineering experience, including full-stack depth (backend, APIs, and Mobile)
• 3 years in an engineering leadership role with direct reports, hiring, growing, and evaluating engineers
• Proven ability to build high-performing engineering teams, not just manage them
• Hands-on experience delivering AI/ML capabilities: LLM APIs, embeddings, RAG patterns, agent workflows, or intelligent automation
• Experience with cloud-native application patterns, microservices, middleware, CI/CD, automation
• Strong executive communication skills; comfortable influencing at the VP and C-suite level
• Ability to hold technical credibility while operating at a strategic altitude