Senior Manager, Lead Gen AI System Architect, AI Institute, Engineering, AI & Data, Technology & Tra

As a Lead GenAI System Architect, you will solve our clients' most challenging business problems by applying Generative AI and other ML techniques to design, deliver and operate robust and cutting-edge solutions. In this role, you may be expected to:

• Engage directly with senior client stakeholders and internal leadership teams to shape, define, and deliver transformative AI and Generative 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, actively 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.

You will be working with clients and other third parties, as well as Deloitte teams from across the Firm. You will have the opportunity to work with a huge variety of interesting, international, and world-leading clients who are navigating an evolving marketplace where Generative AI is taking artificial intelligence to a new level. This technology has the potential to transform various industries by creating higher-order opportunities such as new services, business models, and improved productivity across the value chain. You will have a degree of technical knowledge, as well as the ability to communicate to business users., We are looking for candidates who are able to demonstrate skills and experience in some of the following, * PhD or equivalent in Computer Science, Machine Learning, Artificial Intelligence, or a related discipline, or equivalent preferred.

• Outstanding 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 in applying AI and Generative AI within a regulated or data-rich industry (e.g., financial services, healthcare, or similar).
• 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 Certifications) and deep understanding of technical courses (e.g., Andrew Ng's Coursera Courses, Andrei Karpathy's Tutorials) highly desirable.

TECHNICAL PROFICIENCY

• Demonstrated success leading the 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 strongly preferred. Background in Traditional ML/AI is preferred.
• Deep understanding of LLMs, prompt engineering, RAG pipelines, vector databases, and 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 is 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.

Deloitte drives progress. Our firms around the world help our clients become market leaders wherever they compete. Deloitte invests in outstanding people with diverse talents and backgrounds, empowering them to achieve more than they can elsewhere. Our work combines consulting with action and integrity. We believe that when our clients and society are stronger, so are we.