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Job Title: Sr. AI Engineer - Large Language Models (LLMs) Experience: 5+ years Key Responsibilities Fine-tuning LLMs: Develop, train, and fine-tune large language models to meet specific client and business requirements. Perform domain adaptation using specialized datasets for improved model relevance and accuracy. LLM Deployment Design and implement scalable, resource-effective deployments of LLMs for production environments. Optimize model inference for low latency while maintaining high accuracy. LLM Agent Development Build intelligent agents leveraging LLMs to automate workflows and support complex tasks. Integrate LLMs with external systems and APIs for enhanced functionality. RAG Implementation Implement retrieval-augmented generation (RAG) techniques to improve LLM performance on knowledge-intensive tasks. Integrate document retrieval systems and knowledge bases into LLM workflows. Collaboration & Communication: Work closely with cross-functional teams, including data scientists, engineers, and domain experts. Present findings and technical designs to stakeholders in a explicit and concise manner. Qualifications Bachelors or Masters degree in Computer Science, AI, Machine Learning, or a related field. Proven experience in fine-tuning and deploying large language models (e.g., GPT, Llama, T5, etc.). Expertise in optimization techniques for memory management and latency reduction. Proficiency in machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, Hugging Face Transformers). Hands-on experience with deploying AI models in scalable architectures (e.g., Kubernetes, Docker, cloud platforms like AWS/GCP/Azure). Knowledge of NLP and deep learning algorithms. Preferred Skills Experience with distributed training and fine-tuning of LLMs. Familiarity with MLOps tools and pipelines. Knowledge of publishing workflows and challenges in the research domain. Strong understanding of retrieval-augmented generation (RAG) techniques and their applications. Solid programming skills in Python or similar languages. .
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.