Lead Software Engineer, AI & Machine Learning

What you'll do

• Define and maintain scalable reference architectures, implementation patterns, and standards for AI and intelligent automation.
• Establish and reinforce Responsible AI governance, including bias mitigation, data quality, and lifecycle management practices.
• Drive enterprise adoption of AI-assisted engineering practices to improve code quality, delivery speed, and operational outcomes.
• Promote shared tooling and reusable capabilities to improve time-to-market and consistency across federated teams.
• Provide advisory support to delivery teams to strengthen design decisions, implementation quality, and operational readiness.
• Promote secure, resilient, and scalable engineering practices across cloud, APIs, and integration patterns.
• Lead a community of practice to share patterns and drive continuous improvement across distributed teams.

What we're looking for

• Formal training or certification on software engineering concepts and 5+ years of applied experience.
• Demonstrated ability to influence and align senior stakeholders across multiple teams in a large, complex organization without direct authority.
• Experience operating within an enterprise enablement function or center of excellence model focused on standards, governance, and scaled adoption.
• Strong understanding of AI/machine learning, generative AI, natural language processing, and intelligent automation concepts.
• Solid grounding in modern engineering practices, including software development life cycle, scalable system design, and operational resilience.
• Experience designing or governing cloud-based architectures leveraging APIs, microservices, and integration patterns at enterprise scale.
• Proven ability to define and embed Responsible AI governance, including bias mitigation, data quality, and lifecycle management.
• Experience leading the use of approved AI-assisted software development tools and coaching engineers on safe, compliant adoption.