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What You will be Doing Design, develop, and deploy Agentic AI and Generative AI (GenAI) solutions for enterprise use cases, including information extraction, workflow automation and predictive modelling. Research and evaluate the latest AI models, tools, skills, frameworks, and coding agents to identify suitable technologies for business requirements. Build AI applications using modern LLM frameworks and orchestrate multi-agent workflows where appropriate. Establish evaluation methodologies, observability, and AI guardrails to ensure reliable, secure, and responsible AI systems. Collaborate with software engineers and product teams to integrate AI capabilities into web and mobile applications. Optimize AI application performance, cost, latency, and user experience through continuous experimentation and iteration. Document technical designs, best practices, and reusable AI components. Who is Our Right Fit Bachelor's degree in Computer Science, Information Technology, Software Engineering, Data Science, Mathematics, Statistics, or a related discipline. 1–2 years of experience in AI software development, machine learning or related fields. (Fresh graduates are also welcome) Hands-on experience building AI applications with coding agents such as Claude Code, Codex, OpenCode, Cursor, or similar AI-assisted development tools. Familiarity with LLM application frameworks such as LangChain, LangGraph, LlamaIndex, or comparable orchestration frameworks. Understanding of prompt engineering, context engineering, RAG (Retrieval-Augmented Generation), and evaluation techniques for LLM applications. Experience with AI observability, testing, monitoring, and guardrails to improve model quality and reliability is an advantage. Familiarity with Python and modern AI/ML libraries (e.g. PyTorch, Transformers, OpenAI SDK, Anthropic SDK, or similar). Basic understanding of REST APIs, Git, Docker, and cloud platforms (AWS, Azure, or GCP) is a plus. Familiarity with e-commerce platforms and online business workflows is an advantage. Strong analytical and problem-solving skills with a proactive, self-driven learning mindset in a rapidly evolving AI landscape. Good command of written and spoken Cantonese, English, and Mandarin.
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.