🎁 Before you apply, rehearse this interview. Create your free WorkMundi account and get an Interview Training on HelpsYouSpeak — no cost, no card. I want my training →
Company Overview We're a workforce solutions partner that helps companies find the right people for hard-to-fill technical roles. Right now, we're working on behalf of one of our clients, an organization in the insurance and financial technology space, to fill a Senior Gen-AI Developer opening. The role is fully remote for candidates based in India, and our client is open to structuring it as full-time, part-time, or contract work depending on what suits the right candidate. Job Summary We are looking for an experienced Senior GenAI Developer to architect, build, and deploy enterprise-grade Generative AI solutions. The ideal candidate should possess strong expertise in Python backend development, Large Language Models (LLMs), and modern AI technologies, with recognised proficiency providing scalable, production-ready AI applications. Key Responsibilities Architect, develop, and deploy end-to-end Generative AI solutions by leveraging Large Language Models (LLMs), Retrieval-Augmented Generation (RAG) frameworks, and other advanced AI technologies. Design and build scalable, secure, and high-performance backend services using Python and FastAPI to power AI-driven applications and enterprise solutions. Build and optimize retrieval pipelines using vector databases and frameworks such as LangChain. Develop, integrate, and deploy AI-powered applications using Azure AI services, including Azure OpenAI, Azure AI Search (formerly Cognitive Search), and related cloud-based AI capabilities. Develop intelligent Copilot-style assistants to automate workflows and enhance user productivity. Design, evaluate, and optimize prompts while implementing model fine-tuning strategies to enhance the accuracy, efficiency, scalability, and cost-effectiveness of Generative AI solutions. Establish production-ready AI environments by implementing CI/CD pipelines, automated monitoring, logging, observability, and evaluation frameworks to ensure reliable, secure, and scalable AI deployments. Collaborate with cross-functional teams, including product managers, data scientists, and frontend developers, to deliver end-to-end AI solutions. Required Skills At least four years of software development experience, complemented by extensive hands-on expertise in Python programming and backend development. Proven hands-on experience designing and building enterprise-grade AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG) architectures, and contemporary Generative AI technologies. Proficiency in FastAPI or similar backend frameworks. Experience with LangChain or equivalent orchestration frameworks. Comprehensive knowledge of the Azure AI ecosystem, including Azure OpenAI, Azure AI Search, and related Azure AI services for developing scalable, cloud-native AI solutions. Expertise in developing AI-powered assistants, Copilot solutions, or conversational AI applications using Large Language Models (LLMs) and related AI frameworks. Solid understanding of REST APIs, microservices, and scalable system design. Hands-on expertise with vector databases such as Pinecone, FAISS, or similar platforms to support semantic search, embedding management, and high-performance RAG implementations. AI Experience Extensive hands-on experience designing and developing Generative AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG) pipelines, and advanced prompt engineering techniques. Practical experience deploying AI solutions on Azure OpenAI and Cognitive Search. Experience fine-tuning Large Language Models (LLMs) or working with open-source foundation models is highly desirable and considered an added advantage. Managerial Experience This is an individual contributor role centered on hands-on technical expertise, and previous people management experience is not a prerequisite. Comfortable collaborating across product, data science, and frontend teams to deliver end-to-end solutions. Operational Experience Practical experience delivering production-grade AI applications by integrating CI/CD automation, observability, monitoring, logging, and evaluation frameworks to support secure, scalable, and resilient deployments. Proven prior experience to MLOps practices and AI model lifecycle management will give an edge amongst others. Experience building enterprise-grade AI applications with security and compliance considerations is a plus. Qualifications Any graduate degree (undergraduate degree in any discipline). 4+ years of professional software development experience, supported by advanced proficiency in Python for building scalable, high-performance applications. Certifications Azure AI Engineer Associate or an equivalent Azure/AI certification is a plus, though not mandatory. Good to Have Hands-on exposure to MLOps methodologies and AI model lifecycle processes .
Here's where they are and how to stand out in your next interview.
24.795Jobs
9.577IN
74%EN
That number includes positions in India (9,577), Poland (3,429), the United States (1,753), Singapore (787), and Brazil (779). If you're looking to move or work remotely, check which countries match your goals — then filter WorkMundi by location to see what's actually hiring near you.
Most developer ads you'll see are written in English: 18,397 of the 24,795. That doesn't tell you whether the job itself requires you to speak English or work in English daily, so read each posting carefully. Don't assume the language of the ad matches the language of the team.
The employers posting the most developer roles are Link Group (369 jobs), Upvanta (257), jobgether (226), and OfferZen (212). If you're applying to any of these, research their hiring patterns. They move fast and post often, which means they're either scaling hard or replacing people who didn't fit.
In your interview, expect this: 'Walk me through the last time you had to debug something that took you more than an hour. What was it, what did you try first, and what would you do differently?' Hiring managers ask this to see if you think systematically or just try random fixes. Have a real example ready with specifics.