Assistant Vice President, GT-Tools, L1 & Testing MY (AI Enablement & Applied GenAI Engineer)

Job Description :

Job Purpose .
We are seeking a hands-on AI Enablement & Applied GenAI Engineer to make AI genuinely usable and adopted across CIMB by embedding it into our tooling teams already work in Tech Observability, Service Management and Governance, DevOps-CI/CD and Testing - while also building agentic AI workflows and pipelines where no off-the-shelf tool exists. This role bridges platform engineering, developer enablement, and applied GenAI delivery, ensuring AI adoption happens safely, within governance, and with measurable business impact.
Job Description .
Enablement (primary focus)
Deploy and integrate AI tools into GitHub (PR review/summarisation, issue triage), Jira (auto-ticketing, sprint planning assist), and Confluence (auto-drafted documentation, knowledge Q&A).
Build internal playbooks, training material, and support processes so teams adopt AI tools with confidence.
Own governance guardrails for AI tool usage - access control, audit logging, data handling - aligned to CIMB's risk and compliance standards (including BNM RMiT requirements).
Track usage, cost, and reliability of deployed AI integrations, reporting adoption impact to stakeholders.
Applied Building (secondary, as required)
Translate business logic and manual bottlenecks into multi-step agentic workflows using frontier LLMs (Claude, GPT via Bedrock/Vertex or direct API).
Build document parsing and ETL pipelines to structure messy inputs (PDFs, tickets, spreadsheets) into usable knowledge formats.
Design lightweight retrieval architectures (vector search plus relational data) to supply agents with accurate context.
Implement evaluation, tracing, and hallucination guardrails for any workflow pushed to production.
Partner with Enterprise Architecture, Application Support, Infrastructure, GT Governance, and business stakeholders to ensure AI initiatives are reviewed and aligned before deployment.

Key Performance Index/Key Result Areas
Adoption rate: % of target teams actively using deployed AI tools/integrations within 90 days of rollout.
Delivery velocity: number of AI-enabled workflows or automations shipped to production per quarter.
Reliability: uptime/error rate of deployed agentic pipelines and integrations against agreed SLA.
Efficiency impact: measurable reduction in manual effort/turnaround time for processes automated (e.g., ticket triage time, documentation lag).
Governance compliance: zero unresolved audit findings related to AI tool access control, data handling, or RMiT alignment.
Cost efficiency: AI tooling/API spend tracked against budget, with cost-per-workflow optimised quarter over quarter.
Stakeholder satisfaction: feedback score from business/technical stakeholders on enablement support and training
Job Specification .
Qualifications
(Basic Degree/Diploma etc)Bachelor's degree in Computer Science, Information Technology, or related field, or equivalent experience.
Professional Qualification and/or Regulatory, Licensing requirements Cloud certification (AWS, Azure, or GCP) preferred. AI/ML or LLM-specific certifications an advantage.
TOGAF/Archimate exposure a plus but not required.
Relevant Work Experience 3-6+ years of hands-on software engineering experience, with strong proficiency in Python (FastAPI, AsyncIO, Pydantic) or TypeScript/Node.js.
Practical experience integrating tools into Dynatrace, GitHub, Jira, and/or Confluence via APIs and webhooks.
Hands-on experience building agentic or LLM-powered workflows using frontier model APIs (Claude, OpenAI, or similar).
Exposure to a regulated industry (banking/financial services) is an advantage.
Key Dimension of Impact .

Required Competencies and Skills .
Competencies/Skills
(Essential to succeed in this job)
Soft Skills
Ability to turn a vague stakeholder ask into a working, adopted automation.
Bias toward shipping and iterating over building the 'perfect' architecture.
Comfortable acting as translator between business/compliance stakeholders and technical implementation.
Ability to communicate effectively, both verbally and in writing, with technical and non-technical audiences.
Ability to manage multiple competing priorities under pressure.

Technology and Technical
Working experience with LLM APIs and agent frameworks (LangGraph, AutoGen, or custom orchestration).
Experience with GitHub API, Atlassian API (Jira/Confluence), and webhook-based integrations.
Familiarity with vector databases (pgvector, Qdrant, Chroma) and RAG pipeline basics.
Working knowledge of Docker, REST API design, CI/CD, and basic cloud infrastructure (AWS/GCP/Azure).
Understanding of IT governance, access control, and audit requirements in a regulated environment.
Familiarity with emerging AI trends and their practical application within banking and financial services.
Travel Requirements (if any)
Frequency
(Incl typical Destinations and Duration)As required