Verveo Solutions Private Ltd

Job Description- AI / Generative AI Engineer (23 Years Experience) Title : AI / Generative AI Engineer Experience : 2 - 3 years Location : Bangalore Employment Type : Full-time About the Role- We are seeking an AI / Generative AI Engineer to join our ML/AI team. In this role, you will work on building, fine-tuning, and deploying NLP and multimodal models, developing GenAI-driven features, and ensuring their scalability, reliability, and security in production. The position requires a balance of hands-on model development, prompt and dataset engineering, and strong engineering practices. Key Responsibilities Design, fine-tune, and evaluate transformer-based generative models for tasks such as summarization, Q&A, code generation, and RAG. Build and maintain data pipelines for model training and evaluation, including dataset collection, cleaning, labeling, and augmentation. Develop, test, and optimize prompt engineering strategies; track performance drift. Create and manage RAG pipelines (embeddings, vector stores, index creation, and retriever tuning). Containerize ML services using Docker and build deployable inference endpoints with FastAPI / Flask / .NET. Support deployments on Kubernetes, serverless frameworks, or cloud platforms. Implement monitoring, logging, and evaluation metrics to detect performance, data, and feature drift. Collaborate with product and infrastructure teams to integrate AI features into applications with best-in-class security (rate limits, PII redaction, moderation). Stay updated on emerging models and benchmark third-party APIs (OpenAI, Anthropic, Meta, etc.). Create clear documentation, runbooks, and reproducible experimentation workflows. Required Qualifications 2 to 3 years of experience in applied ML, NLP, or generative AI. Strong Python skills with experience in PyTorch (preferred) or TensorFlow. Models: Logistic Regression, Decision Trees, Random Forests, Neural Networks, RNN, LSTM, EncoderDecoder, Attention, Transformers, BERT, GPT Generative AI: OpenAI, Mistral, LLaMA, Gemini, Claude, Hugging Face, RAG, Fine-tuning, AI Agents LLM Tools: LangChain, LangSmith, LangGraph, AutoGen, CrewAI, Azure AI Foundry Vector Databases: FAISS, ChromaDB, Pinecone, Qdrant, Weaviate Backend: FastAPI, Flask, REST APIs, Redis, RabbitMQ, Node.js, WebHooks, Postman, Swagger Understanding of model evaluation metrics (ROUGE, BLEU, Accuracy, F1, safety metrics). Experience with LLM orchestration frameworks (LangChain, LlamaIndex, LangGraph, AutoGen). Preferred / Nice-to-Have- Familiarity with prompt engineering techniques and templates. Experience with cloud platforms (AWS, GCP, Azure) and managed ML services (SageMaker, Vertex AI, Bedrock). Understanding of model security and privacy practices (PII redaction, moderation). Experience with ML monitoring tools (Prometheus, Grafana). Deliverables / KPIs (First 36 Months- Deliver at least one end-to-end GenAI feature (prototype staging) with evaluation results. Set up reproducible fine-tuning pipelines and experiment tracking. Deploy a production-ready inference service with monitoring and cost controls. Create prompt templates with a documented rollback strategy for model updates