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AI Delivery Engineer

Globe Telecom

AI Delivery Engineer

full-timePosted: Aug 19, 2026Updated: Sep 3, 20269F The Globe Tower

Job Description

At Globe, our goal is to create a wonderful world for our people, business, and nation. By uniting people of passion who believe they can make a difference, we are confident that we can achieve this goal. Job Description Own the delivery path between Finance stakeholders and technical teams — translating Finance requirements into scoped work, coordinating execution across technical sections, and keeping concurrent workstreams on track.This is a delivery role at its core: requirements, backlog, sequencing, and stakeholder management. It is technical in the work it manages and in the tools it uses. You will use AI tooling to automate status reporting, tracking, and documentation.There will also be room to do hands-on AI-assisted development — prototypes, data checks, automation, and small data products — depending on your skills and what the workstreams need. This is not the main deliverable, but it is real work and it will grow with the person in the role. Hands-on Python and SQL are a big advantage and will shape how far the role can go.You will work directly with both engineers and Finance business partners.PurposeThis role sits between Finance demand and technical delivery. It scopes the work, sequences it across concurrent workstreams, holds teams to the plan, and stays close enough to the build to know when an estimate does not add up.ResponsibilitiesElicit and document requirements from Finance and Risk stakeholders — user stories, acceptance criteria, process flowsManage intake and backlog; scope, sequence, and prioritize across concurrent workstreamsRun project lifecycles — planning, dependency and risk management, delivery trackingRun delivery cadences — standups, milestone reviews, stakeholder updatesCoordinate dependencies and governance across AI Engineering, Decision Science, and Operations/AutomationCoordinate UAT, acceptance, and handover into BAU supportUse AI tooling to automate status reporting, tracking, and documentationSupport governance requirements — model approvals, data classification, audit documentationEssential SkillsRequirements engineering — turning ambiguous business needs into scoped, testable deliverablesDelivery experience across concurrent technical workstreams, with real dependency and risk managementStakeholder management across Finance, engineering, and cross-functional partnersInfluence without formal authority — driving alignment and accountability across peersWorking knowledge of Finance and Risk use cases and requirementsCredible with technical teams — able to follow technical discussion, challenge estimates, and hold delivery to accountStrong AdvantagePython and SQL for data analysis, automation, and AI-assisted development, ideally hands-onETL pipeline development, data cleansing, scheduling, and data rationalization, ideally hands-onAI-assisted development workflows — agentic coding tools (Claude Code, Copilot), LLM APIs, prompt and context engineeringPlatform familiarity across cloud environments — AWS, GCP, Databricks, and related toolsUsing generative AI tools to support development, documentation, code optimization, testing, and data product deliveryCredit risk domain — portfolio behaviour, collections, provisioning, IFRS 9 ECLRegulated finance delivery — model governance, audit trails, data classificationEqual Opportunity EmployerGlobe’s hiring process promotes equal opportunity to applicants, Any form of discrimination is not tolerated throughout the entire employee lifecycle, including the hiring process such as in posting vacancies, selecting, and interviewing applicants.Globe’s Diversity, Equity and Inclusion Policy Commitment can be accessed hereMake Your Passion Part of Your Profession. Attracting the best and brightest Talents is pivotal to our success. If you are ready to share our purpose of Creating a Globe of Good, explore opportunities with us.

Locations

  • 9F The Globe Tower

Responsibilities

  • Elicit and document requirements from Finance and Risk stakeholders — user stories, acceptance criteria, process flows
  • Manage intake and backlog; scope, sequence, and prioritize across concurrent workstreams
  • Run project lifecycles — planning, dependency and risk management, delivery tracking
  • Run delivery cadences — standups, milestone reviews, stakeholder updates
  • Coordinate dependencies and governance across AI Engineering, Decision Science, and Operations/Automation
  • Coordinate UAT, acceptance, and handover into BAU support
  • Use AI tooling to automate status reporting, tracking, and documentation
  • Support governance requirements — model approvals, data classification, audit documentation

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