We are partnering with a well-established global technology services organisation to appoint a Principal AI Architect.
This is a senior individual contributor role embedded within a global Innovation Hub, where you will serve as a trusted advisor to technology leaders across a wide range of enterprise clients. You will operate at the intersection of Generative AI, cloud architecture, and business transformation by engaging CxO-level stakeholders, shaping AI strategy, and contributing to the organisation's thought leadership agenda.
Responsibilities
- Design and deliver comprehensive AI solution architectures across Edge, on-premises, and Public Cloud environments, ensuring alignment with modern engineering best practices.
- Lead architectural discussions with enterprise clients, providing guidance on AI implementations spanning infrastructure, application, and intelligent agent domains.
- Architect GenAI solutions from ideation to MVP, balancing speed, accuracy, and business value across varied deployment environments.
- Act as a trusted senior advisor to CxO-level stakeholders, providing strategic guidance on Generative AI adoption and its impact at both the employee and organisational level.
- Conduct workshops, briefings, and executive dialogues to educate and guide clients on AI strategy and real-world application.
- Author technical content and represent the organisation at industry events, maintaining a visible presence as a practitioner in the AI and Cloud space.
- Engage multiple client organisations simultaneously, building high-impact consultative relationships while collaborating closely with internal teams and technology partners.
- Stay ahead of emerging trends, maintain hands-on technical credibility, and contribute to mentoring and knowledge-sharing across the wider team.
Requirements
- Degree in Computer Science, Engineering, Information Technology, or a related discipline.
- Expertise across major Public Cloud platforms and coding proficiency in Python, Java, or Go.
- Knowledge of machine learning, GenAI models, NLP, and Deep Learning frameworks (TensorFlow, PyTorch).
- Experience with LLMOps, AI model fine-tuning, and governing AI in production environments.
- Proficiency in data engineering for AI, including preprocessing, feature engineering, and pipeline development.
- Familiarity with Copilot and intelligent agent solutions across engineering and enterprise productivity use cases.
- Knowledge of Responsible AI principles including governance, ethics, and bias mitigation.
- Strategic AI vision and road mapping capability, with enthusiasm for working in a fast-paced, innovation-led environment.
EA Reg No: R1981018 | EA License: 14S7084
