AVP, Tech Lead, Enterprise GenAI Platform, Data Platform, Group Technology (WD88788)

DBS BANK LTD.; Singapore; On-site; SGD 180,000 - 240,000; Full time

Job summary

DBS Bank Ltd. seeks a Tech Lead to own GenAI platform architecture on Google Cloud, focusing on security posture, cost efficiency and scalable data engineering across the bank’s enterprise estate.

You will lead design and operations of GenAI services, IAM, private connectivity, and cost governance while mentoring engineers and collaborating with security, risk and business stakeholders.

Qualifications

• Master's degree in Artificial Intelligence, ML, Data Science or closely related discipline.
• Bachelor's degree in Computer Science, Information Technology or related discipline.
• 10+ years of technology experience, including 3+ years in banking/financial services.
• Google Cloud Certified Professional Cloud Architect (active).
• Hands-on experience designing and operating production GenAI or LLM-based platforms on Google Cloud for enterprise.
• Strong GCP security and networking expertise, including private connectivity to managed services, VPC/subnet design, DNS routing and multi-region architectures, plus IAM and RBAC.
• Solid understanding of LLM cost and capacity management: consumption modelling, reserved vs on-demand capacity, caching and inference cost optimisation.
• Experience delivering AI solutions in isolated or highly restricted environments with security approvals.
• Experience with agent orchestration frameworks and tool-enabled LLM workflows in regulated enterprise settings.
• Strong data engineering background with Apache Spark, including production troubleshooting and SQL.
• Strong programming skills in Python; working knowledge of Java.
• Experience with CI/CD tooling, containerisation and modern observability stacks.
• Strong communication skills with security, risk, vendor and business stakeholders.
• Ability to work proactively and independently in evolving GenAI governance landscape.
• Experience building conversational AI or virtual assistants in an enterprise.
• Experience with on-premise to cloud migration of big data platforms and cost analysis.
• Familiarity with ML frameworks and search/vector retrieval tech is a plus.

Responsibilities

• Lead the architecture, delivery and operation of GenAI services on Google Cloud.
• Design agent and orchestration patterns for LLM-based applications with bank policy compliance.
• Establish secure execution patterns for tool-enabled AI workflows within enterprise boundaries.
• Assess third-party/open-source AI products for deployment in controlled environments and coordinate with vendors.
• Design private, zero-trust connectivity for AI and data services on GCP (private endpoints, VPC, DNS).
• Own identity, access and role-based control models for AI workloads and model endpoints.
• Produce risk assessments and layered security designs; navigate governance processes.
• Forecast LLM consumption and inform capacity commitments and pricing models.
• Reduce inference cost and latency via caching and workload tuning.
• Lead cloud capacity planning and cost-management including on-premise migrations analysis.
• Provide technical leadership over large-scale batch/distributed data pipelines on cloud services.
• Establish platform observability, alerting and reliability targets.
• Mentor engineers, review designs and set standards for AI/data workloads.
• Represent platform in discussions with Security, governance, vendors, stakeholders.
• Participate in Agile delivery and drive engineering excellence.

Skills

Python

SQL

Java

GCP security

Stakeholder comms

Education

Master's degree in AI/ML/Data Science

Bachelor's degree in CS/IT

Tools

CI/CD tooling

Containerisation

Apache Spark

Observability stacks

DNS routing

Job description

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

We offer a competitive salary and benefits package and the professional advantages of a dynamic environment that supports your development and recognises your achievements.