Key Responsibilities:
•    Responsible for designing and delivering hybrid AI Platform.
•    Develop and maintain scalable, efficient and reliable data and AI pipelines.
•    Collaborate with data scientist, data engineers, and central data governance team to align with a standardised data strategy.
•    Design and implement MLOps and LLMOps framework
•    Design and implement automated pipelines for prompting machine learning models to production.
•    Design and implement monitoring strategy for AI Platform and integrate with central observability platform.
•    Ensure AI platform delivery and services meet security and risk requirements and operational SLA.
•    Write and maintain detailed documents for hybrid AI Cloud Platform.
•    Cross-Collaborate with technology and architecture teams to align with best practices and standards.
•    Perform code-reviews ensuring lower tech debt and avoiding spaghetti code.
•    Stay up to date with industry trends, research in artificial intelligence field.
•    Develop and maintain strong relations ships with internal and external stakeholders.

Regulatory & Business Conduct
•    Display exemplary conduct and live by the Group’s Values and Code of Conduct. 
•    Take personal responsibility for embedding the highest standards of ethics, including regulatory and business conduct, across Standard Chartered Bank. This includes understanding and ensuring compliance with, in letter and spirit, all applicable laws, regulations, guidelines and the Group Code of Conduct.
•    Effectively and collaboratively identify, escalate, mitigate and resolve risk, conduct and compliance matters.

Key stakeholders
•    TTO Management Team
•    T&A Management Team
•    CDO
•    Software Engineering Platform Teams
•    Business, Regional & Country CIOs & COOs
•    Operational, Technology & Cyber Risk 
•    Chief Data Office
•    Group and Country Compliance & Regulators 
•    Group Internal Audit
•    Group Operational Risk

Qualifications

•    Experience: 8-10 years of experience in AI and machine learning engineering, with a proven track record of delivering complex AI projects.
•    Technical Expertise: Strong proficiency in machine learning frameworks (e.g., TensorFlow, PyTorch), MLOps tools (e.g., MLflow, Kubeflow), and cloud platforms and infrastructure as code (e.g., AWS, Azure).
•    GPU Expertise: Hands-on experience with GPU computing and optimization for AI workloads.
•    Programming Skills: Proficiency in programming languages such as Python, Golang
•    Problem-Solving: Excellent analytical and problem-solving skills, with the ability to think critically and creatively.
•    Communication: Strong interpersonal and communication skills, with the ability to work effectively in a collaborative team environment