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We are looking for a Data Scientist / Gen AI Engineer with 3 years of experience in developing AI-driven solutions, with a strong focus on Generative AI and LLM-based applications. The role requires ownership of projects end-to-end and the ability to translate business problems into scalable AI solutions. Key Responsibilities - Build and deploy Generative AI applications using Large Language Models (LLMs) - Design and implement RAG (Retrieval-Augmented Generation) pipelines - Develop AI agents and agentic workflows capable of multi-step reasoning, tool usage, and task automation - Work with embeddings, semantic search, and vector databases - Perform data preparation and basic feature engineering for ML tasks - Develop and deploy machine learning models for prediction/recommendation use cases - Collaborate with product and engineering teams to deliver AI solutions - Monitor and improve model/LLM performance in production Required Skills: Generative AI / LLMs - Hands-on experience with LLM APIs (e.g., Open AI, Google, Microsoft Azure AI) - Robust understanding of prompt engineering and evaluation - Experience building RAG systems and working with vector databases (e.g., FAISS, Pinecone, We aviate) - Familiarity with embeddings and semantic search Programming & ML - Proficiency in Python - Experience with basic machine learning (classification, regression, clustering) - Familiarity with libraries like pandas, NumPy, scikit-learn Data & Deployment - Good SQL skills - Experience deploying models or APIs (basic MLOps understanding) - Familiarity with cloud platforms (AWS / GCP / Azure) or Docker Good to Have - Experience with frameworks like LangChain or LlamaIndex - Exposure to production AI systems or real-world deployments - Basic data visualization (Tableau, Power BI, or Python libraries) .
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.
