At ABB, we help industries run leaner and cleaner—and every person here makes that happen. You’ll be empowered to lead, supported to grow, and proud of the impact we create together. Join us and help run what runs the world. Senior Operation Manager for D\&A **Mission of the Role** Do you enjoy turning real business challenges into working AI solutions? Would you like to do it at a global company that is changing its industry with new technology? ABB is looking for a **hands\-on AI/ML Engineer** to join our **Information Systems (IS)** . This is a **specialist role where you build the solutions yourself** . It is not a coordination or management role. You will work with the business to understand its needs and then find the best answer. That could be a predictive model, an LLM or SLM, an AI agent, a GenAI application, analytics, automation or a conventional solution. You will take that solution from idea to production and keep it running well in operations. If you have experience with **Azure AI/ML, Snowflake, GenAI and MLOps** , and you want to own solutions from start to finish across both Dev and Ops, this opportunity is for you! **Work model:** Hybrid **Responsibilities** **Business understanding and solution design** * Work with business stakeholders and Data Analysts to clarify needs, requirements, expected outcomes, success measures, data and context requirements, risks and ownership. * Decide which approach fits each business problem best: AI/ML, GenAI, analytics, automation or a conventional solution. This includes choosing the right model type (ML, LLM, SLM), the right agent design and the right technology. * Design scalable solutions that follow enterprise architecture, security and governance standards, with guidance from the Advanced Analytics Architect and platform architects. **Build and deploy** * Develop, validate and deploy production\-ready AI/ML solutions using Python, SQL, Azure Machine Learning, Microsoft Foundry and other approved technologies. * Build ML and GenAI applications, including predictive models, RAG, embeddings, vector search, prompt/context engineering, AI agents, APIs, orchestration, retrieval and enterprise data integrations. * Build and integrate LLM\-based solutions and conversational agents using Microsoft Foundry, Azure OpenAI and, where appropriate, Copilot Studio and Power Platform. Support Copilot and other AI platforms, such as Anthropic models. * Use enterprise data from SAP and Salesforce to build predictive models, GenAI applications and AI agents that deliver measurable business value. * Build secure, reliable data ingestion and processing from Snowflake and other enterprise sources, with attention to data quality, lineage, access control and cost efficiency. * Apply Snowflake AI/ML capabilities, including Snowpark ML, Cortex AI, Cortex Search and AI Functions. * Develop reusable components and automated pipelines for data preparation, feature engineering, training, inference, evaluation, testing, deployment and retraining, using CI/CD and version control. **Evaluate, operate and improve (DevOps / MLOps / AIOps)** * Evaluate model accuracy, explainability, grounding, agent behaviour, safety, business value, performance, reliability and cost. * Set up and run MLOps/AIOps practices: monitoring, drift detection, cost monitoring, root\-cause analysis, retraining and continuous improvement. You own both development and operations. * Contribute to production readiness, operational handover, incident and problem analysis, monitoring design and reliable day\-to\-day operations. * Apply Responsible AI, information security, privacy, compliance, identity and access management, secrets management and other ABB requirements within your solution scope. **Ownership and collaboration** * Own your deliverables end to end. Estimate effort, manage priorities, report progress and risks, and work independently within the agreed architecture and platform guardrails. * Work closely with Data Analysts, Data Scientists, Snowflake Developers, Data Engineers, Power BI/Fabric Developers, platform specialists and domain experts. * Document solution logic, assumptions, limitations, evaluation results and operational requirements. Contribute reusable assets, engineering practices, knowledge sharing and mentoring. **Requirements** **Education and experience** * Master's degree in Computer Science, Data Science, Statistics, Applied Mathematics, Engineering or a related technical field, or equivalent practical experience. * 4–6 years of hands\-on experience in Data Science, AI/ML Engineering, analytics engineering or related roles, including taking AI/ML solutions to production. * Experience delivering AI/ML solutions end to end: business requirements, data preparation, development, validation, deployment and monitoring. **Technical Skills** * Practical Python and SQL skills for data preparation, model development, API integration, testing and implementation. * Hands\-on experience with Azu