AI Engineering - Solutions Architect

HPE Networking’s Digital Experience & Automation team seeks an AI Engineering - Solutions Architect to build scalable AI solutions for digital support and services. The team uses AI, automation and data-driven insights to improve self-service, shorten resolution times and identify opportunities across customer and operational data. This is a full-time, 40-hour-per-week role in Bengaluru, Karnātaka, India, designed as on-site with work primarily from an HPE office.

Responsibilities

• Lead the architecture and development of large-scale solutions using machine learning, deep learning and generative AI, integrating models and techniques into the software development life cycle. Work with engineering, business and technology teams to translate requirements into scalable, efficient and robust systems.
• Develop and optimize models through data preprocessing, feature engineering, algorithm and model selection, hyperparameter tuning and training on large datasets. Deploy models to production, integrate them with existing systems, and monitor and improve accuracy, performance, scalability and security.
• Build data extraction, transformation and loading infrastructure and analytics tools. Analyze customer cases, hardware and software bugs, machine logs and operational metrics to identify patterns, provide business insights and find automation opportunities.
• Research emerging AI methods; lead code and design reviews, set implementation standards with engineering leadership, mentor colleagues and present technical and business recommendations to senior stakeholders.

Requirements

• 11+ years of experience in a data science role and a graduate degree in Computer Science, Statistics, Informatics, Information Systems or another quantitative field. The posting also specifies 6+ years building data pipelines for data science-driven solutions and deployment of multiple solutions to production.
• In-depth knowledge of one or more of classical machine learning, NLP, generative AI, agentic AI or MCP; experience with large language models and conversational AI; and a strong foundation in mathematics and statistics. Experience with technical-support data, large or unstructured datasets, root-cause analysis, data transformation and cross-functional collaboration is required.
• Hands-on coding for large-scale data processing and model development, preferably in Python. Familiarity with machine-learning or statistical tools such as NumPy, Scikit-learn, MLlib and TensorFlow, plus experience with Databricks, Snowflake, AWS services, big-data and streaming tools, and SQL and NoSQL databases. Knowledge of SDLC and Agile principles and strong interpersonal, written, verbal and presentation skills are also sought.

HPE describes health and wellbeing benefits and personal and professional development programs.