Generative AI Engineer

4 days ago


bangalore, India MASSIVUE Full time

Job Title: Generative AI EngineerExperience: 5 – 7 YearsLocation: Delhi / Gurugram / Bangalore / Pune / HyderabadNotice Period: Immediate to 15 DaysAbout the Role:We are looking for an experiencedGenerative AI Engineerto design, develop, and deploy AI solutions leveraging large language models (LLMs), transformers, and modern GenAI frameworks. The ideal candidate will have strong Python skills, deep understanding of AI/ML, and hands-on experience building production-grade GenAI applications.Key Responsibilities:Design and implement end-to-end Generative AI solutions using LLMs (GPT, LLaMA, Claude, etc.).Build, fine-tune, and optimize transformer-based models for specific business use cases.Develop prompt engineering strategies to improve model accuracy and response quality.Integrate LLMs into applications using frameworks like LangChain, Hugging Face, LlamaIndex etc.Work on retrieval-augmented generation (RAG) pipelines and vector databases (Pinecone, Chroma, FAISS).Deploy GenAI solutions on cloud platforms (AWS, Azure, GCP) using containerization and CI/CD pipelines.Collaborate with data scientists, backend engineers, and product teams to deliver scalable AI-powered products.Monitor, evaluate, and continuously improve model performance and reliability.Required Skills & Experience:5–7 years of software engineering / AI experience with at least 2+ years in Generative AI / LLM projects .Strong programming skills in Python and experience with ML/AI libraries ( PyTorch, TensorFlow, Transformers ).Expertise in LLMs, NLP, prompt engineering, fine-tuning , and model deployment.Hands-on experience with LangChain, Hugging Face, LlamaIndex , and vector databases.Knowledge of RAG pipelines, embeddings, and semantic search .Strong understanding of API integration, microservices, and cloud platforms (AWS/Azure/GCP) .Familiarity with MLOps tools (MLflow, Kubeflow, Docker, Kubernetes) is a plus.Good to Have:Experience with multi-modal AI (text, image, speech).Understanding of model evaluation metrics and bias mitigation techniques.Contributions to open-source GenAI projects or custom LLM training experience.



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