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AI/ML Engineer (LLMs & Generative AI) Location: Kolkata (Onsite) Experience: 26 Years Employment Type: Full-Time About the Role We are looking for a highly motivated AI/ML Engineer with hands-on experience in Generative AI, Large Language Models (LLMs), and Machine Learning. The ideal candidate should possess strong software engineering skills and practical experience in developing, deploying, and optimizing AI-powered applications using modern ML frameworks and GenAI technologies. Key Responsibilities Design, develop, and deploy AI/ML solutions using Python. Build and optimize applications leveraging Large Language Models (LLMs). Develop and fine-tune prompts for different AI use cases through effective prompt engineering. Design and implement Retrieval-Augmented Generation (RAG) pipelines. Develop and integrate AI agents for intelligent automation and workflow orchestration. Work with vector databases for semantic search and knowledge retrieval. Evaluate model performance using appropriate metrics and implement continuous improvements. Build scalable, production-ready AI applications following MLOps best practices. Collaborate with cross-functional teams to understand business requirements and translate them into AI solutions. Write clean, maintainable, and well-documented code following software engineering best practices. Stay updated with the latest advancements in AI, machine learning, and Generative AI technologies. Required Skills & Qualifications 26 years of experience in AI/ML or related software development roles. Strong programming skills in Python. Hands-on experience with machine learning frameworks such as PyTorch and/or TensorFlow. Practical experience working with Large Language Models (LLMs). Strong understanding of Prompt Engineering techniques. Experience in building Retrieval-Augmented Generation (RAG) applications. Experience developing AI Agents using modern AI frameworks. Hands-on experience with Vector Databases (such as Pinecone, Chroma, FAISS, Weaviate, or Milvus). Knowledge of Model Evaluation methodologies and performance optimization. Good understanding of MLOps fundamentals, including model deployment, monitoring, and lifecycle management. Strong analytical, debugging, and problem-solving skills. Good understanding of software engineering principles, data structures, algorithms, and API development. Excellent communication and collaboration skills. Preferred Qualifications Experience with cloud platforms such as AWS, Azure, or Google Cloud. Exposure to Docker, Kubernetes, and CI/CD pipelines. Familiarity with LangChain, LlamaIndex, CrewAI, AutoGen, or similar AI orchestration frameworks. Experience with REST APIs, FastAPI, or Flask. Knowledge of Git version control and Agile development methodologies. What We Offer Opportunity to work on cutting-edge AI and Generative AI projects. Exposure to modern AI tools, frameworks, and technologies. Collaborative and innovation-driven work environment. Career growth opportunities and continuous learning. Competitive compensation and benefits. .
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.