Job
Description
BMC AMI Cost and Capacity Management - As digitization increases, so does the complexity of managing mainframe capacity and costs. BMC AMI Cost and Capacity portfolio increases availability, predicts capacity bottlenecks before they occur, and optimizes mainframe software costs. Here is how, through this exciting role, YOU will contribute to BMC's and your own success: We are seeking a Python with AI/ML Developer to join a highly motivated team responsible for developing and maintaining innovation for mainframe capacity and cost management. As an Application Developer at BMC, you will be responsible for: Developing and integrating AI/ML models with a focus on Generative AI (GenAI), Retrieval-Augmented Generation (RAG), and Vector Databases to enhance intelligent decision-making. Building scalable AI pipelines for real-time and batch inference, optimizing model performance, and deploying AI-driven applications. Implementing RAG-based architectures using LLMs (Large Language Models) for intelligent search, chatbot development, and knowledge management. Utilizing vector databases (e.g., FAISS, ChromaDB, Weaviate, Pinecone) to enable efficient similarity search and AI-driven recommendations. Developing modern web applications using Angular to create interactive and AI-powered user interfaces. Developing APIs and microservices to expose AI/ML models for enterprise applications. Processing and analyzing structured & unstructured data, including text, images, and time-series data for AI/ML applications. Optimizing ML models for performance and scalability, ensuring low latency and high availability in production. Staying updated with advancements in GenAI, NLP, transformers, and deep learning architectures to drive innovation. Collaborating with cross-functional teams to integrate AI capabilities into existing applications and workflows. To ensure youre set up for success, you will bring the following skillset & experience: Strong proficiency in Python and AI/ML frameworks like TensorFlow, PyTorch, Hugging Face Transformers, LangChain. Experience with Vector Databases (FAISS, ChromaDB, Weaviate, Pinecone) for semantic search and embeddings. Hands-on expertise in LLMs (GPT, LLaMA, Mistral, Claude, etc.) and fine-tuning/customizing models. Proficiency in Retrieval-Augmented Generation (RAG) and prompt engineering for AI-driven applications. Experience with Angular for developing interactive web applications. Experience with RESTful APIs, FastAPI, Flask, or Django for AI model serving. Working knowledge of SQL and NoSQL databases for AI/ML applications. Hands-on experience with Git/GitHub, Docker, and Kubernetes for AI/ML model deployment. Whilst these are nice to have, our team can help you develop in the following skills: Experience with knowledge graphs, semantic search, and enterprise AI applications. Additional experience with .NET v7+ and cross-platform .NET development would be helpful. Exposure to IBM z/OS mainframe environments and AI-driven optimization for legacy systems. Background in statistical data analysis, reinforcement learning, or advanced ML techniques.
