GenAI Engineer, Software Specialist Engineer

GenAI Engineer Software Specialist Engineer II Experience:{ 5.5-8.5 Years}** Location: Hyderabad / Bengaluru Job Description: We are looking for a GenAI Engineer with strong software engineering experience to design, develop, and deploy enterprise-grade AI solutions. The ideal candidate should have hands-on experience in Generative AI, AI/ML, LLMs, Python, Cloud, and modern software development practices. Skills Required: 5.5+ years of Software Engineering/AI experience with minimum 2 years in GenAI. Strong in Python, OOPs, Data Structures & Algorithms . Hands-on experience with OpenAI, Claude, Gemini, LangChain, AI Agents, RAG, Prompt Engineering, Fine-tuning, Vector Databases . Experience in TensorFlow, PyTorch, Keras, NLP, Machine Learning . Knowledge of React, Angular, Node.js, Java, C#, .NET Core, Golang . Experience with SQL/NoSQL , REST APIs, Microservices. Cloud experience on Azure, AWS, or GCP . Good understanding of Agile, DevSecOps, CI/CD, GitHub, Azure DevOps, SonarQube, SRE . Experience in designing, developing, testing, deploying, and supporting scalable AI applications. Strong communication, collaboration, and problem-solving skills. Key Responsibilities Design, develop, test, deploy, and maintain enterprise-grade GenAI applications. Build intelligent AI Agents, Agentic AI workflows, and Retrieval-Augmented Generation (RAG) solutions. Develop scalable backend services and APIs using Python and modern programming languages. Work extensively with OpenAI, Azure OpenAI, Claude, Gemini, and open-source LLMs. Implement Prompt Engineering, Fine-Tuning, Embeddings, Vector Search, and LLM Optimization techniques. Build applications using LangChain, LangGraph, Semantic Kernel, LlamaIndex, CrewAI, AutoGen, or similar AI frameworks. Design and integrate Vector Databases such as Pinecone, ChromaDB, FAISS, Milvus, Weaviate, or Azure AI Search. Develop NLP, Machine Learning, and Deep Learning models where required. Translate business requirements into scalable technical solutions. Create technical specifications and deliver high-quality, maintainable, reusable, and scalable code. Perform code reviews, unit testing, debugging, integration testing, and production support. Ensure software quality, performance, security, and maintainability throughout the SDLC. Build cloud-native applications using Microservices, Containers, APIs, and Event-driven architectures. Collaborate with Product Managers, Architects, UX Designers, DevOps Engineers, QA, and Business Teams. Follow Agile, Scrum, Lean, XP, SAFe, DevSecOps, CI/CD, and SRE methodologies. Work with GitHub, Azure DevOps, SonarQube, Jenkins, Git, and automated deployment pipelines. Participate in continuous learning and adopt emerging AI/ML technologies. Drive engineering excellence, innovation, technical quality, and customer-centric product delivery.