VP/AVP, Tech Lead, Enterprise GenAI Platform

About the role

The Data Platform team owns the bank's enterprise Generative AI capabilities and the cloud data infrastructure supporting business units across the bank. It is looking for a Tech Lead to own the architecture, security posture and cost efficiency of its GenAI platform on Google Cloud. The role combines hands-on AI engineering with cloud architecture, security and networking design, cloud financial management and technology risk governance, and provides senior technical leadership over the platform's data engineering estate.

Key responsibilities

• Lead the architecture, delivery and operation of enterprise GenAI services on Google Cloud, including knowledge search, retrieval-augmented generation and conversational assistants.
• Design agent and orchestration patterns for LLM-based applications that comply with bank policy on autonomous systems and enforce access controls on retrieved data.
• Establish secure execution patterns for tool-enabled AI workflows so that outputs and actions stay within enterprise isolation boundaries.
• Assess third-party and open-source AI products for deployment in tightly controlled environments and work with vendors on architectural changes.
• Design private, zero-trust connectivity for AI and data services on GCP, covering private endpoints, VPC and subnet design, DNS-based traffic steering and regional endpoint strategy.
• Own identity, access and role-based control models for AI workloads, model endpoints and data access.
• Produce technical risk assessments and layered security designs, and take solutions through Information Security, Technology Risk and Architecture governance.
• Forecast LLM consumption and inference demand, reduce inference cost and latency through caching, model selection and right-sizing, and lead annual cloud capacity and budget planning.
• Prepare cost-of-ownership analyses and business cases for on-premise to cloud migrations for senior management.
• Lead large-scale batch and distributed data pipelines and their migration to managed cloud services, establish observability, alerting and reliability targets, mentor engineers and set engineering standards.
• Represent the platform with Information Security, cloud governance, vendors and business stakeholders, and participate in Agile delivery.

Required profile

• Master's degree in AI, Machine Learning, Data Science or a closely related discipline, or Bachelor's in Computer Science, Information Technology or a related discipline.
• Minimum 10 years of technology experience, including at least 3 years in banking or financial services.
• Google Cloud Certified Professional Cloud Architect (active credential required).
• Experience delivering AI solutions in isolated or highly restricted environments and securing Information Security and Technology Risk approvals.
• Experience with agent orchestration frameworks and tool-enabled LLM workflows in a regulated enterprise setting.
• Strong data engineering background with distributed processing frameworks such as Apache Spark, including production troubleshooting and performance tuning, and proficiency in SQL.
• Strong programming skills in Python; working knowledge of Java.
• Experience with CI/CD tooling, containerisation and modern observability stacks.
• Experience building conversational AI or virtual assistants, and on-premise to cloud migration of big data platforms with cost analysis, are highly desirable.

Required skills

• Google Cloud Platform security and networking: private connectivity, VPC and subnet design, DNS routing, multi-region architectures, IAM and role-based access.
• LLM cost and capacity management: consumption modelling, reserved versus on-demand capacity, caching and inference cost optimisation.
• Apache Spark, SQL, Python, CI/CD and containerisation.