Lead Software Engineer

As Lead AI/ML Engineer at Faculty, you shape the technical direction of complex AI projects and ensure scalable, production-ready models. You will lead large-scale AI platforms for public sector and high-risk environments, aligning ML, data science, and DevOps to deliver high-value outputs. You’ll mentor a distributed engineering team, establish coding and deployment standards, and translate business strategy into tangible technical roadmaps. This role offers a chance to drive responsible AI initiatives that impact government services and citizen outcomes. You’ll work in a fast-growing, mission-driven environment that values curiosity and impact, with opportunities to influence architecture,

• Unlimited Annual Leave Policy
• Private healthcare and dental
• Enhanced parental leave
• Family-Friendly Flexibility & Flexible working
• Sanctus Coaching
• Hybrid Working

• Set the technical direction for complex software projects to support long-term product and client goals
• Drive development of shared libraries and microservices to accelerate delivery across client engagements
• Oversee delivery of large-scale AI-powered platforms in high-risk environments
• Facilitate alignment between ML, Data Science, and DevOps to build reliable software foundations
• Manage and coach a distributed engineering team, aligning development goals with organizational growth
• Establish enterprise-wide standards for code delivery, testing, and system documentation
• Lead hiring processes to build a world-class software engineering team

• Deep expertise across the application lifecycle to set high standards for system integration and end-user software quality
• Ability to design large-scale, complex software ecosystems with authority to justify critical architectural trade-offs in high-stakes environments
• Define production readiness standards and deployment protocols across diverse client engagements
• Translate commercial strategy into technical roadmaps and ensure AI workstreams are accurately estimated and integrated
• Architecturally direct development of products leveraging autonomous AI agents for robustness and integration
• Confident communicator able to convey technical roadmaps and architectural risks to commercial partners and leadership

• Confident communicator
• Leadership and coaching
• Cross-functional collaboration
• AI/ML engineering
• Software architecture for large-scale systems
• Production deployment and reliability