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AI Engineer / Generative AI Engineer (Python, LLM, RAG) Location: Bangalore / Hyderabad / Pune (Hybrid) Experience: 5 - 10 Years Joining Preference: Immediate Joiners / Candidates serving up to 30 days' notice Job Summary We are looking for a highly skilled AI Engineer / Generative AI Engineer with robust expertise in Python, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and Agentic AI. The ideal candidate will be responsible for designing and building scalable AI-powered applications, intelligent agents, and enterprise-grade GenAI solutions using modern AI frameworks and cloud-native technologies. Key Responsibilities - Design, develop, and deploy enterprise-grade AI applications using Python and modern backend frameworks. - Build intelligent applications leveraging Large Language Models (LLMs), prompt engineering, and agentic AI architectures. - Design and implement Retrieval-Augmented Generation (RAG) pipelines using vector databases and knowledge retrieval systems. - Develop scalable REST APIs and event-driven microservices to integrate AI capabilities with enterprise applications. - Work with frameworks such as LangChain, LangGraph, or similar orchestration frameworks for LLM-based applications. - Optimize AI models for performance, scalability, reliability, and security. - Collaborate with product managers, architects, and business stakeholders to translate business requirements into AI-driven solutions. - Deploy and manage AI applications using cloud-native technologies and containerized environments. - Follow software engineering best practices, including testing, CI/CD, and code reviews. Required Skills - Strong hands-on experience with Python and backend application development. - Experience building applications using Large Language Models (LLMs). - Strong knowledge of Prompt Engineering and Agentic AI architectures. - Hands-on experience with Retrieval-Augmented Generation (RAG), Vector Databases, and enterprise knowledge retrieval systems. - Experience using LangChain, LangGraph, or similar LLM orchestration frameworks. - Good understanding of REST APIs, API design, and event-driven architectures. - Experience developing cloud-native microservices and distributed applications. - Strong analytical, debugging, and problem-solving skills. - Excellent communication and stakeholder management skills. Preferred Skills - Experience in Banking, Financial Services, or FinTech domains. - Exposure to Document AI, Intelligent Document Processing (IDP), or Fraud Detection solutions. - Hands-on experience with Docker and Kubernetes. - Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform (GCP). - Familiarity with CI/CD pipelines and DevOps practices. .
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.