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AI/ML Engineer (Python + LLM)1 Key Responsibilities: Experience - 4-8 years. Location - Hyderabad preferred Customer Interview - Yes Strong hands-on experience in Python development, building data-driven applications, creating APIs, debugging, testing, and deploying production-ready solutions. Must have experience in developing data-based chatbots using Large Language Models, Retrieval-Augmented Generation, and structured/unstructured data sources. Must have hands-on experience with LLM workflows including prompt engineering, fine-tuning, model evaluation, response quality analysis, and performance optimization. Should have strong experience in data processing and preprocessing using Python libraries such as Pandas, NumPy, and other relevant data-handling frameworks. Must have experience in FastAPI and REST API development, including creating, consuming, testing, and maintaining scalable APIs. Should be able to design and build backend services that interact with databases, vector stores, external APIs, and other data sources. Having experience in LLM evaluation frameworks, test datasets, automated evaluation pipelines, and quality benchmarking will be highly preferred. Should have hands-on experience in writing unit tests, integration tests, and API tests using Pytest or similar Python testing frameworks. Experience in deployment of Python applications, APIs, and AI/ML services on cloud or server environments. Should be able to write efficient, reusable, testable, and scalable Python code following best development practices. Good understanding of data cleaning, transformation, chunking, embedding generation, and preparation of data for chatbot or AI/ML workflows. Exposure to microservices-based architecture and backend application design will be preferred. Ability to debug and optimize applications for performance, reliability, and scalability. Should have basic knowledge of frontend technologies and be able to collaborate with frontend developers for integrating APIs into web applications. Ability to integrate multiple data sources into a unified chatbot or AI-driven system. Good problem-solving skills with the ability to work independently on AI/ML, data, and backend engineering tasks. Must-Have Skills: Python, FastAPI, REST APIs, Data Processing, Data Preprocessing, LLMs, Data-Based Chatbots, Fine-Tuning, LLM Evaluations, Pytest, API Testing, Deployment. Good-to-Have Skills: Frontend basics, Microservices, Vector Databases, RAG pipelines, Docker, Cloud Deployment, SQL/NoSQL Databases, CI/CD, LangChain/LangGraph, OpenAI/HuggingFace APIs.
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.
