🎁 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 →
We are partnering with a leading enterprise organization undergoing significant investment in Artificial Intelligence, Data, and Digital Innovation. They are looking for an experienced AI Engineer to design, build, and scale enterprise-grade Generative AI solutions that deliver measurable business impact. This position will focus on developing production-ready LLM applications, Retrieval-Augmented Generation (RAG) platforms, AI agents, and intelligent automation services that enhance decision-making, operational efficiency, and customer engagement. You will work at the intersection of AI, software engineering, cloud technologies, and data platforms, collaborating with multidisciplinary teams to take AI products from proof-of-concept through to enterprise-scale deployment. Responsibilities of the Role: Design, develop, and deploy end-to-end Generative AI applications leveraging Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) architectures. Build scalable AI platforms, APIs, and microservices that integrate AI capabilities into enterprise systems and business workflows. Develop and optimize document ingestion, processing, embedding generation, vector indexing, semantic search, and retrieval pipelines. Implement prompt engineering strategies, evaluation frameworks, AI guardrails, and monitoring tools to ensure reliability, accuracy, and responsible AI adoption. Design and maintain AI infrastructure, including vector databases, knowledge repositories, model serving environments, and deployment pipelines. Collaborate with software engineers, data scientists, product teams, and business stakeholders to deliver AI-driven solutions aligned with business objectives. Research and evaluate emerging AI technologies, open-source models, agentic frameworks, and best practices across the GenAI ecosystem. Optimize system performance across retrieval quality, latency, scalability, cost efficiency, and user experience through benchmarking and experimentation. Contribute to AI platform governance, security standards, compliance requirements, and responsible AI initiatives. Promote engineering excellence through CI/CD practices, MLOps frameworks, and cloud-native deployment methodologies. Required Skills for the Role: Degree in Computer Science, Artificial Intelligence, Machine Learning, Engineering, Mathematics, or related discipline. Advanced qualifications are advantageous. Minimum 3 years of experience in AI Engineering, Machine Learning Engineering, Software Engineering, Data Science, or related technical domains. Proven experience designing and implementing production-scale Generative AI, LLM, RAG, or AI Agent solutions. Strong programming skills in Python with solid understanding of software engineering principles, system design, testing, and API development. Hands-on experience with modern AI frameworks and orchestration tools such as: LangChain LangGraph LlamaIndex Haystack Semantic Kernel Experience working with vector databases and semantic search technologies, including: Pinecone Weaviate FAISS Milvus Chroma Familiarity with leading AI ecosystems and foundation models, including OpenAI, Azure OpenAI, Anthropic Claude, Gemini, Hugging Face, and open-source LLMs. Experience designing and deploying cloud-native applications on AWS, Azure, or Google Cloud Platform (GCP). Knowledge of MLOps, CI/CD pipelines, Kubernetes, Docker, and scalable model deployment architectures. Exposure to AI Agents, tool orchestration, function calling, Model Context Protocol (MCP), and multi-agent systems is highly advantageous. Strong SQL skills and foundational knowledge of data engineering concepts. Excellent communication skills.
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.