🎁 Before you apply, rehearse this interview. Create your free WorkMundi account and get an Interview Training on HelpsYouSpeak — no cost, no card. I want my training →
Job Description Role Overview As a AI Transformation Engineer , you will help translate AI and automation ideas into working solutions that improve how StarHub's network and operations teams run day to day. You will work alongside senior engineers to build, test, and deploy practical AI use cases — from automating manual workflows to surfacing insights from network and operational data. This is a hands-on, learning-focused role for an early-career engineer. You will get broad exposure across the technology transformation — data pipelines, machine learning, LLM-based tooling, and process automation — while building the judgement to deliver solutions that are reliable, compliant, and genuinely useful. Key Responsibilities 1. Building & Delivering AI Solutions Support the design, development, and testing of AI and automation use cases under the guidance of senior engineers. Build and maintain data pipelines and scripts that prepare, clean, and transform network and operational data for AI models. Develop and refine prompts, retrieval (RAG) workflows, and lightweight integrations for LLM-based internal tools. 2. Automation & Process Improvement Identify repetitive manual tasks across engineering and operations that are good candidates for automation. Implement workflow automations and monitor them in production, escalating issues and iterating on improvements. 3. Data, Testing & Documentation Run experiments, evaluate model outputs, and help measure accuracy, latency, and reliability against clear success criteria. Document solutions, data sources, and design decisions so work is reproducible and auditable. 4. Collaboration & Compliance Work closely with data, network, and platform engineers, and take part in code reviews and knowledge-sharing. Follow PDPA and internal data-governance practices when handling customer and network data. Qualifications Degree (or final-year / recent graduate) in Computer Science, Data Science, Engineering, or a related field. 0–2 years; internships, academic projects, or personal projects in AI, data, or automation are welcomed. Working knowledge of Python, ML and AI; basic understanding of how LLMs and SLMs are used in applications. Exposure to telecom or network data, cloud platforms, or LLM tooling (e.g. RAG, prompting) through study or projects. Foundational familiarity in: Python/AI Agents/Git/Version Control/Rest APIs/ML Fundamentals/LLMs/SLMs/Prompting/RAG Basics/Pandas/NumPy/Data pipelines/Cloud Basics/Automation Scripting/Data Visualization
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.