Lead GenAI System Architect
We are seeking an experienced Lead GenAI System Architect in the AI Institute, a centre of excellence in Deloitte’s Engineering, AI & Data service offering.
You will work with clients, third parties, and Deloitte teams across the firm to design, deliver, and operate generative AI solutions that transform organisations.
Responsibilities
- 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, 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.
Education & Experience
- PhD in Computer Science, Machine Learning, Artificial Intelligence, or a related discipline 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.
- 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 Certifications) and deep understanding of technical courses 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.
- 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.
Working Location
Based in London with a hybrid working model, combining office, virtual collaboration spaces, client sites and remote work as required.
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