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Role Description The AI Engineer (Full Stack Engineering) designs, develops, tests, deploys, and maintains modern cloud-native applications using an AI-first engineering model. This role requires strong full-stack capability, upfront architecture and specification skills, responsible use of AI coding assistants, and ownership of quality, security, reliability, and production readiness. Key Responsibilities Apply AI-first engineering practices across discovery, requirements, design, development, testing, deployment, operations, and continuous improvement. Translate business outcomes into clear technical specifications, architecture decisions, NFRs, design notes, and acceptance criteria. Build secure, scalable, resilient, observable, and maintainable full-stack solutions. Use AI responsibly to improve engineering productivity and software delivery quality. Partner with product, architecture, security, operations, and business teams to deliver aligned outcomes. Support incident resolution, automation, simplification, and continuous improvement activities. Candidate Qualifications Bachelor’s degree in Computer Science, Engineering, Information Technology, or equivalent experience. At least 3 years of experience developing enterprise applications using modern full-stack, API, data, and cloud technologies. Hands-on experience with AI-assisted software delivery, GitHub Enterprise, and GitHub Copilot. Exposure to Azure AI Foundry, Copilot SDK, Semantic Kernel, AI agents, RAG, and LLM application patterns is preferred. Strong knowledge of Agile, DevOps, CI/CD, automated testing, API-first development, domain-driven design, and shift-left quality and security practices. Ability to clearly articulate requirements, design intent, constraints, trade-offs, and outcomes for people and AI-assisted platforms. Tech Stack AI & Developer Productivity: GitHub Enterprise, GitHub Copilot, Azure AI Foundry, Microsoft Copilot ecosystem, Copilot SDK, Semantic Kernel, AI agents, RAG, LLM patterns. Cloud & Architecture: Microsoft Azure, cloud-native architecture, microservices, APIs, containers/Kubernetes, event-driven architecture, observability. Delivery & Engineering: Azure DevOps, Git, CI/CD, automated testing, SonarQube, secure coding, infrastructure as code, Agile, DDD, API-first, ADRs, NFRs. Development & Operations: Java, Spring Boot, ReactJS, HTML, JavaScript, mobile frameworks, SQL/NoSQL, authentication/authorization, API management, Veracode, Azure Application Insights, Elastic, logging, and monitoring.
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.