Job Purpose
The Data Platform team owns the bank's enterprise Generative AI capabilities and the cloud data infrastructure that supports business units across the bank. We are looking for a Tech Lead to take ownership of the architecture, security posture and cost efficiency of our 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 across 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 appropriate access controls on retrieved data. - Establish secure execution patterns for tool-enabled AI workflows so that generated outputs and actions
remain within enterprise isolation boundaries. - Assess third-party and open-source AI products for deployment in isolated, tightly controlled
environments, and work with vendors on the architectural changes needed to meet bank standards. - Design private, zero-trust connectivity for AI and data services on GCP, covering private endpoint
access, 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 across model tiers to inform capacity commitments
and pricing model selection. - Reduce inference cost and latency through caching strategies, model selection and workload
right-sizing. - Lead annual cloud capacity and budget planning for the platform and drive elimination of cloud waste.
Prepare cost-of-ownership analyses and business cases for on-premise to cloud migrations for senior
management. - Provide technical leadership over large-scale batch and distributed data pipelines and their migration to
managed cloud services, including resolution of production performance issues. - Establish platform observability, alerting and reliability targets.
- Mentor engineers, review designs and set engineering standards for AI and data workloads.
- Represent the platform in discussions with Information Security, cloud governance functions, vendors
and business stakeholders. - Participate actively in Agile delivery and contribute to engineering excellence across the organisation.
Job Requirements
- Master's degree in Artificial Intelligence, Machine Learning, Data Science or a closely related discipline;
Bachelor's degree in Computer Science, Information Technology or a related discipline. - Minimum 10 years of technology experience, including at least 3 years within the banking or financial
services industry. - Google Cloud Certified Professional Cloud Architect (active credential required).
- Hands-on experience designing and operating production GenAI or LLM-based platforms on Google
Cloud for enterprise users. - Strong GCP security and networking expertise, including private connectivity to managed services, VPC
and subnet design, DNS routing and multi-region architectures, together with IAM and role-based
access design. - Solid understanding of LLM cost and capacity management: consumption modelling, reserved versus
on-demand capacity trade-offs, caching approaches and inference cost optimisation. - Experience delivering AI solutions in isolated or highly restricted environments and securing Information
Security and Technology Risk approvals for them. - 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.
- Strong analytical, problem-solving and communication skills, with the ability to engage security, risk,
vendor and business stakeholders. - Ability to work proactively and independently, and to operate with ambiguity in an evolving GenAI
governance landscape. - Experience building conversational AI or virtual assistants in an enterprise setting is highly desirable.
- Experience with on-premise to cloud migration of big data platforms and associated cost analysis is
highly desirable. - Familiarity with machine learning frameworks and search or vector retrieval technologies is a plus
Location:
DBS Asia Hub
Job:
Technology
Schedule:
Regular
Employee Status:
Full time
