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About the Role We are seeking an experienced GenAI / AI-ML Engineer to design, develop, and deploy scalable Generative AI and Machine Learning solutions. In this role, you will build modern RAG pipelines, deploy multi-agent workflows, fine-tune models, and integrate scalable backend APIs for enterprise-grade applications. Note: This position is open exclusively to local candidates in Noida/NCR who are immediate joiners or currently serving their notice period. Key Responsibilities GenAI & Agentic Systems: Develop LLM-powered applications utilizing prompt engineering, AI agents, and multi-agent workflows (LangChain, LangGraph).RAG Pipelines: Build, optimize, and evaluate Retrieval-Augmented Generation (RAG) pipelines using modern vector databases and frameworks like RAGAS.Backend Integration: Write robust Python code and build high-performance REST APIs using FastAPI to support AI models in production.ML/DL Engineering: Design end-to-end data preprocessing, feature engineering, fine-tuning, and model evaluation pipelines using Scikit-learn, PyTorch, TensorFlow, and Keras.Cloud & DevOps: Containerize applications using Docker and deploy scalable models on AWS (SageMaker, Bedrock, EC2, S3) with CI/CD integration.Collaboration: Partner with Data Engineering, DevOps, and Product teams to ensure reliability, security, and performance of production environments.Requirements Experience: 46 years in core Machine Learning / Deep Learning, with at least 1+ years of dedicated hands-on experience in GenAI/LLM projects.Programming & Backend: Strong proficiency in Python, SQL, and framework expertise with FastAPI.GenAI Stack: Hands-on experience with OpenAI APIs, Hugging Face, LangChain, LangGraph, LangSmith, and vector databases (Pinecone, FAISS).Evaluation Metrics: Practical experience with evaluation frameworks (RAGAS, BLEU, ROUGE) and semantic search architectures.Cloud Infrastructure: Solid background with AWS services (EC2, S3, SageMaker, Bedrock), Docker, and Git.Availability: Immediate joiners or candidates currently serving their notice period based in Noida/NCR.Compensation: 1,800,000.00 - 2,000,000.00 per year Application Question(s): Are you based in Noida/NCR and available as an immediate joiner (or currently serving your notice period) Do you have at least 1 year of hands-on experience building GenAI applications using LangChain, LangGraph, or multi-agent workflows Which vector databases and RAG evaluation tools have you used in production (e.g., Pinecone, FAISS, RAGAS) How many years of experience do you have building production REST APIs using FastAPI in Python Work Location: In person .
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.
