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