VP/AVP, Tech Lead, Enterprise GenAI Platform, Data Platform, Group Technology

DBS; Singapore; Hybrid; SGD 180,000 - 320,000; Full time

Job summary

DBS is seeking a VP/AVP Tech Lead to own the architecture, security posture and cost efficiency of the Enterprise GenAI Platform on Google Cloud. The role blends hands-on AI engineering with cloud architecture, risk governance and senior technical leadership across the data engineering estate.

You will lead the design of scalable LLM-based services, ensure enterprise isolation boundaries, and drive cost-effective capacity planning while collaborating with Security, Cloud Governance and

Qualifications

• Master's degree in AI/ML/Data Science or closely related field.
• Minimum 10 years of technology experience, incl. 3 years in banking/financial services.
• Google Cloud Certified Professional Cloud Architect (active).
• Hands-on experience designing and operating GenAI/LLM platforms on Google Cloud for enterprise.
• Strong GCP security and networking expertise, incl. private connectivity to managed services, VPC/subnet design, DNS routing, multi-region architecture.
• Experience with AI solutions in isolated environments and securing approvals from Info Security/Tech Risk.

Responsibilities

• Lead architecture, delivery and operation of GenAI services on Google Cloud.
• Design agent/orchestration patterns for LLM apps with enterprise access controls.
• Establish secure execution patterns for tool-enabled AI workflows within isolation boundaries.
• Assess 3rd-party AI products for isolated deployments and advise architectural changes.
• Design private, zero-trust connectivity for AI/data services on GCP (private endpoints, DNS, regional endpoints).
• Own IAM/RBAC models for AI workloads and data access.
• Produce risk assessments and security designs for governance approvals.
• Forecast LLM consumption and capacity for pricing and budgets.
• Reduce inference cost/latency via caching, model choice and right-sizing.
• Lead cloud capacity and budget planning; prepare on-prem to cloud migrations business cases.
• Provide tech leadership for large-scale batch/distributed pipelines, migration to managed cloud services.
• Establish observability, alerting and reliability targets.
• Mentor engineers and set engineering standards for AI/data workloads.
• Represent platform in security/governance/vendor discussions; engage stakeholders.
• Participate in Agile delivery and engineering excellence.

Skills

GCP architecture

Security engineering

Cost optimisation

Distributed data pipelines

Python programming

SQL

Java

CI/CD tooling

Spark

Cloud security

IAM RBAC

VPC design

Agile delivery

Leadership

Google Cloud Architect credential

Education

Master's degree in AI/ML/Data Science

Bachelor's degree in CS/IT

Tools

Apache Spark

SQL

Python

Java

CI/CD tooling

Containerisation

Job description

## VP/AVP, Tech Lead, Enterprise GenAI Platform, Data Platform, Group TechnologyApply: Singapore - East: Full time: Posted Today: WD88788**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