Pata platform engineer- AI / Associate Director

Job Description

We are currently seeking an experienced professional to join our team in the role of Associate Director, Software Engineering.

The Data and AI Tech Lead provides technical leadership for delivering data, analytics and artificial intelligence capabilities within HSBC. This role blends hands-on engineering with delivery accountability to take initiatives from discovery and design through to production adoption.

You’ll translate business needs into practical technology solutions and partner closely with stakeholders to deliver outcomes that matter. The work spans modern data engineering and enterprise AI including generative AI use cases such as retrieval-augmented generation (RAG) and conversational applications.

Responsibilities

• Own end-to-end delivery of data and AI initiatives from discovery and design through to production adoption
• Set technical direction for engineering and delivery teams and unblock complex engineering and architecture issues
• Partner with business stakeholders, product owners and technology partners to shape requirements into deliverable solutions
• Design and implement AI solutions including RAG pipelines, conversational applications and enterprise AI use cases
• Apply hands-on expertise with AI tools and platforms including Microsoft Copilot and comparable generative AI technologies
• Shape data and AI architecture across ingestion, processing, storage, governance, model integration, monitoring and deployment
• Use cloud and DevOps capabilities across platforms such as Google Cloud Platform (GCP) and Amazon Web Services (AWS)
• Manage delivery risks, dependencies, priorities and technical decisions and escalate issues when needed

Requirements

• Bring proven delivery experience across data, analytics, AI or machine learning solutions in a complex enterprise environment
• Demonstrate hands-on capability with generative AI and large language model solutions
• Apply practical experience building RAG pipelines, vector search, prompt engineering and model integration
• Use AI assistants and productivity tools such as Microsoft Copilot in real delivery contexts
• Show strong grounding in data engineering including data pipelines, APIs and integration patterns
• Apply working knowledge of GCP and/or AWS including relevant data, AI, security and compute services
• Use DevOps practices and tooling including CI/CD automation to improve reliability and delivery pace
• Convert business requirements into clear technical designs and delivered outcomes in Agile or iterative environments