Lead GenAI System Architect: Transform AI at Scale

We are seeking experienced Lead GenAI System Architect(s) in the AI Institute, a centre of excellence in Deloitte's Engineering, AI & Data service offering. You will work with clients and third parties, as well as Deloitte teams, to design, develop, and operate advanced Generative AI solutions that transform organisations.

Your role:

• Engage directly with senior client stakeholders and internal leadership teams to shape, define, and deliver transformative AI strategies aligned with business goals.
• Lead the design, development, and implementation of advanced AI pipelines, encompassing data acquisition, preprocessing, feature engineering, model development, evaluation, and secure deployment at scale.
• Oversee the development and operationalisation of state‑of‑the‑art AI models, including large language models (LLMs), diffusion models, and other generative techniques, ensuring scalability, efficiency, and robustness.
• Stay at the forefront of AI and Generative AI research, evaluating emerging technologies and integrating relevant advancements into client solutions and internal frameworks.
• Mentor and guide cross‑functional AI teams, promoting knowledge sharing, reusable assets, and best practices to drive delivery excellence and sustainable growth.

Qualifications – Education & Experience:

• PhD or equivalent in Computer Science, Machine Learning, Artificial Intelligence, or a related discipline, or equivalent preferred.
• Exceptional candidates with strong quantitative, computer science, or engineering backgrounds in a related field will also be considered.
• Extensive experience designing, developing, and deploying enterprise‑grade AI/ML solutions, including experience managing technical teams and stakeholder relationships.
• Deep domain expertise applying AI and Generative AI within a regulated or data‑rich industry (e.g., financial services, healthcare).
• Demonstrated track record of thought leadership in AI/ML, evidenced by patents, publications, or significant open‑source contributions.
• Relevant industry certifications (AWS/Google/Azure/IBM ML or equivalent) and deep understanding of technical courses (e.g., Andrew Ng's Coursera Courses, Andrei Karpathy's Tutorials) highly desirable.

Qualifications – Technical Proficiency:

• Demonstrated success leading end‑to‑end development and deployment of complex, production‑grade AI/ML and Generative AI solutions; evidence of real‑world impact highly desirable.
• Expert‑level proficiency in Python and modern AI/ML frameworks, including PyTorch, TensorFlow, and specialised Generative AI libraries (LangChain, LangGraph or related open‑source toolkits).
• Deep understanding of LLMs, prompt engineering, RAG pipelines, vector databases, generative architectures; related security practices and evaluation procedures; hands‑on experience fine‑tuning, deploying, and evaluating large‑scale production systems.
• Hands‑on experience designing and implementing robust evaluation frameworks, security best practices, and ethical guardrails to ensure safe, responsible, and compliant deployment of AI and Generative AI systems.
• Broad experience across major cloud platforms (AWS, Azure, GCP) with Generative AI services; cloud‑agnostic experience preferred.
• Strong grasp of MLOps/LLMOps principles, including CI/CD for ML, model monitoring, and governance frameworks.
• Proficiency with large‑scale data processing and storage technologies (SQL, Spark, Hadoop) is a plus.
• Excellent stakeholder management and communication skills, with proven ability to translate complex AI concepts for diverse audiences.

Location: Based in London with hybrid working flexibility.