Director, Software Engineering, AI

Here's what you'll do

• Technical and Team Leadership:
  • Set technical direction and guide engineering decisions for the delivery of AI-enabled product capabilities, ensuring scalability, reliability, and security.
  • Establish and refine SDLC processes that accommodate for the fast rate of change of the AI technological landscape without sacrificing the overall delivery quality.
  • Ensure the implementation of continuous integration, continuous delivery, and other modern engineering practices.
  • Identify and implement opportunities for process improvement, optimizing development lifecycles and mitigating technical risks.
  • Drive the prioritization of feature delivery, while ensuring the alignment with business goals through the performance indicators evaluation.
  • Ensure ethical AI practices are embedded throughout the development process, addressing concerns like data privacy, bias, and transparency.
  • Champion the culture of collaboration, ownership and engineering excellence throughout the AI engineering organization.
• Cross-functional Collaboration and Stakeholder Management:
  • Communicate complex technical concepts and project updates clearly and effectively to both technical and non-technical audiences, including senior leadership.
  • Act as a technical authority in customer engagements, understanding needs and ensuring solutions deliver tangible business impact.
  • Collaborate with Product Management to develop the vision, strategy, and roadmap for AI-driven initiatives, aligning with overall short and long term business objectives.

Here's what you'll need

• Strong technical background with extensive experience in software development (10+ years) and delivery of production-grade capabilities. Exceptional software architecture and system design skills.
• Proven experience in a leadership role, experience managing multiple teams and managing managers (5+ years).
• Deep understanding of the SDLC and experience with agile methodologies. Demonstrable ability to define and implement processes that result in positive product delivery outcomes.
• Expertise in AI/ML fundamentals, including model training, optimization, deployment, and monitoring.
• Experience with cloud computing platforms (AWS, Azure, or Google Cloud Platform) and modern data ecosystems.
• Exceptional communication, collaboration, and stakeholder management skills.