AI Engineering Team Lead

About the role and team
As an AI Technical Lead within Deloitte's Engineering practice, you will provide technical leadership across generative and agentic AI engagements. You will be responsible for solution architecture, delivery governance, technical decision-making, stakeholder engagement, and mentoring engineering teams while remaining close to the technology.
You will lead the design and implementation of enterprise-scale AI solutions that combine foundation models, modern cloud platforms, enterprise data ecosystems, and responsible AI practices.
Working closely with Directors, Partners, architects, data specialists and client stakeholders, you will help shape AI strategies, establish delivery standards, and accelerate the adoption of AI across Deloitte and our clients.
A week in the life of a AI Technical Lead might look like:
Engineering end-to-end projects and developing sprint deliverables in generative and agentic AI, developing innovative solutions using existing digital platforms and foundation models from concept to deployment, in a fast-paced dynamic environment.
Collaborating with cross-functional Deloitte teams to identify technical requirements and architecting and deploying AI solutions in complex environments that meet those requirements.
Identifying patterns and best practices for AI solutions that can be repeated across domains and platforms.
Leading the technical design and architecture of generative and agentic AI solutions for Deloitte and client engagements.
Acting as the technical authority across multiple workstreams, providing guidance on architecture, model selection, engineering approaches and platform decisions.
Engaging with senior client stakeholders to understand business challenges and translate them into pragmatic AI solutions.
Leading technical teams through discovery, design, delivery and deployment phases.
Establishing engineering standards covering AI governance, observability, responsible AI, security, scalability and operational support.
Providing technical oversight of LLMOps practices, including evaluation frameworks, monitoring, testing, prompt management and optimisation.
Contributing to proposals, solution estimates, technical assurance reviews and client presentations.
Developing reusable assets, accelerators and reference architectures that can be leveraged across Deloitte engagements.
Coaching engineers, architects and consultants while fostering a collaborative, high-performing culture.
Remaining hands-on with emerging technologies where required while maintaining awareness of evolving AI capabilities and market trends.
Enough about us, let’s talk about you. You are someone with:
Significant experience leading multidisciplinary technology delivery teams in consulting, professional services or technology organisations.
Proven experience architecting and delivering cloud-native solutions using Azure, AWS, GCP or OCI.
Demonstrated experience designing and deploying generative AI, agentic AI or intelligent automation solutions in enterprise environments.
The ability to balance strategic architecture decisions with pragmatic delivery outcomes.
Experience establishing engineering standards, governance frameworks and delivery best practices.
Strong understanding of modern software engineering practices including DevOps, CI/CD, infrastructure as code and cloud-native architectures.
Experience working directly with senior stakeholders and translating business objectives into technical roadmaps.
Excellent communication, facilitation and stakeholder management skills.
A passion for developing people, growing capability and contributing to a positive team culture.
A commitment to continuous learning and staying current with emerging AI technologies.
Preferred
Experience leading AI programmes or AI capability development initiatives.
Experience contributing to proposals, pre-sales activities and solution shaping.
Experience defining AI governance, risk and responsible AI frameworks.
Relevant AWS, Azure, GCP or AI-related certifications.

Employment type
Full-time

Work arrangement
No