Assoc, AI Core DevOps Engineer, Data Platform, Group Technology

DBS Bank Ltd; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

DBS Bank Ltd in Singapore is seeking an experienced AI and DevOps engineer to collaborate with SMEs across finance, security, risk, and application teams. You will map current processes, translate business needs into AI and agent-based use cases, prototype solutions, and advance them toward production.

You'll develop models for cost forecasting and anomaly detection, design safe AI agents with guardrails, and build end-to-end services deployed on GCP and on-prem, with strong emphasis on

Qualifications

• 3-6 years of experience in DevOps, platform, MLOps, or AI engineering.
• Hands-on experience building ML models or LLM-based applications in Python.
• Exposure to RAG pipelines, vector databases, LLM evaluation, and guardrails.
• Experience building interactive web applications with React and data visualization libraries.
• GCP experience (GKE, Vertex AI) and self-managed Kubernetes.

Responsibilities

• Map current processes with SMEs to identify data sources and pain points.
• Turn business needs into AI and agent-based use cases and prototypes.
• Develop AI models for cost forecasting, anomaly detection, and risk scoring.
• Design AI agents that summarize posture, flag issues, and trigger actions.
• Build production-grade services with guardrails and audit trails.
• Own deliverables end to end from plan to handover.

Skills

Ownership mindset

Communication

Analytical thinking

Problem solving

Tools

Python

React

Flask/FastAPI

GKE

Vertex AI

Kubernetes

vLLM/Triton/KServe

SQL/MySQL

BigQuery

Trino/Presto

Grafana

Job description

Working with subject-matter experts (SMEs) across finance, infrastructure, security, risk, and application teams, you will learn their processes and constraints to design AI and agent-based solutions that give the organisation clear, actionable insight. We want a resource who takes full ownership of their work and is keen to learn how enterprise architecture comes together.

• Work with SMEs across domains to map their current processes, data sources, pain points, and limitations.
• Turn business needs into AI and agentic use cases, then propose, prototype, and refine solutions with the team.
• Develop AI models for cost forecasting, anomaly detection, utilisation right-sizing, and compliance risk scoring.
• Design and build AI agents that can answer questions, summarise posture, flag issues, and recommend or trigger actions (for example, "Which applications are over-provisioned and missing DR coverage?").
• Put guardrails, evaluation, human-in-the-loop approvals, and audit trails in place so agents are safe and trustworthy at enterprise scale.
• Turn successful prototypes into reusable, production-grade services and reference patterns.

Enterprise 360° AI Initiative

• Work with SMEs across domains to map their current processes, data sources, pain points, and limitations.
• Turn business needs into AI and agentic use cases, then propose, prototype, and refine solutions with the team.
• Develop AI models for cost forecasting, anomaly detection, utilisation right-sizing, and compliance risk scoring.
• Design and build AI agents that can answer questions, summarise posture, flag issues, and recommend or trigger actions (for example, "Which applications are over-provisioned and missing DR coverage?").
• Put guardrails, evaluation, human-in-the-loop approvals, and audit trails in place so agents are safe and trustworthy at enterprise scale.
• Turn successful prototypes into reusable, production-grade services and reference patterns.

Full-Stack Application Development

• Build and maintain interactive React-based dashboards and tools that surface AI-driven insights to business users, including data visualisation with charting libraries.
• Develop and extend Python/Flask RESTful APIs that integrate with databases, AI services, and external data sources, with attention to error handling, caching, and security.
• Work across the full stack - from responsive, user-facing UIs to backend SQL query generation, API design, and server-side business logic.

Architecture and Stakeholder Engagement

• Contribute to group-wide initiatives as part of the Architecture team, from early assessment to delivery.
• Help write solution designs, reference architectures, technical standards, and decision records.
• Present findings, recommendations, and trade-offs clearly to both technical and business audiences.

AI Platform Engineering (GCP and On-Prem)

• Build CI/CD and MLOps pipelines for models, agents, and microservices, deploying to GKE and on-prem clusters.
• Deploy and scale model and LLM serving (for example vLLM, Triton, or KServe) and Vertex AI endpoints.
• Integrate with GitOps (ArgoCD or Flux) and observability platforms (Prometheus, Grafana, Cloud Monitoring, OpenTelemetry).
• Apply security and compliance standards across all deployments.

Ownership & Execution

• Own your deliverables end to end: plan, build, document, hand over, and support them.
• Take initiative, raise risks early, suggest improvements, and follow through without being asked.
• Keep up with developments in AI, agents, and infrastructure, and bring useful ideas back to the team.

Job Requirements

• 3-6 years of experience in DevOps, platform, MLOps, or AI engineering.
• Hands-on experience building ML models or LLM-based applications in Python.
• Exposure to RAG pipelines, vector databases, LLM evaluation, and guardrails. Exposure to agentic frameworks and patterns such as LangGraph, Google ADK, Vertex AI Agent Builder, CrewAI, tool/function calling, or MCP.
• Experience building interactive web applications with React (hooks, context, component composition) and modern JavaScript/ES6+, including data visualisation with charting libraries such as Recharts or Chart.js.
• Hands-on backend development with Python/Flask (or FastAPI/Django), building RESTful APIs that integrate with databases (MySQL, Trino/Presto) and external services, with attention to error handling, caching, and security. Comfortable working across the full stack - from designing responsive, user-facing dashboards and forms (Bootstrap, styled-components) to implementing API endpoints, SQL query generation, and server-side business logic.
• Hands-on GCP experience (GKE, Vertex AI, BigQuery, IAM) and experience with self-managed Kubernetes.
• Solid SQL and data-wrangling skills for pulling together data from many enterprise sources.
• The confidence to engage SMEs, ask good questions, and turn their processes into technical solutions.
• A strong sense of ownership, accountability, and follow-through. Clear written and verbal communication, alongside a genuine curiosity to learn enterprise architecture.

Location

DBS Asia Hub

Job

Technology

Schedule

Regular

Employee Status

Full time