AI Engineering - Solutions Architect

AI Engineering - Solutions Architect

This role has been designed as ‘’Onsite’ with an expectation that you will primarily work from an HPE office.

Who We Are:

Hewlett Packard Enterprise is the global edge-to-cloud company advancing the way people live and work. We help companies connect, protect, analyze, and act on their data and applications wherever they live, from edge to cloud, so they can turn insights into outcomes at the speed required to thrive in today’s complex world. Our culture thrives on finding new and better ways to accelerate what’s next. We know varied backgrounds are valued and succeed here. We have the flexibility to manage our work and personal needs. We make bold moves, together, and are a force for good. If you are looking to stretch and grow your career our culture will embrace you. Open up opportunities with HPE.

Job Description:

Job Family Definition:

At HPE Networking, the Digital Experience & Automation (DEA) team is reimagining how people experience support and services in a digital‑first world—setting new standards for the future of networking. We enable customers, partners, and employees through AI‑driven tools and modern platforms, transforming support into a unified, efficient, and simple experience that drives measurable value. Our mission is grounded in innovation with purpose: applying automation, AI, and data‑driven insights to simplify journeys, reduce friction, and create meaningful outcomes at every touchpoint.

DEA’s charter is to discover, evaluate, and scale solutions that embed intelligent technology into every interaction—delivering proactive and predictive experiences that shorten resolution times and accelerate task completion. We partner closely with technology providers, engineering, and business teams to deliver seamless omnichannel experiences and enable business transformation through data engineering, process optimization, and automation. Our work is fuelled by a passion for self‑service, intelligent automation, and building digital experiences that are intuitive, scalable, and human‑centric.

Management Level Definition:

Contributions include applying developed subject matter expertise to solve common and sometimes complex technical problems and recommending alternatives where necessary. Might act as project lead and provide assistance to lower level professionals. Exercises independent judgment and consults with others to determine best method for accomplishing work and achieving objectives.

What You'll Do:

• Leads as well as develops scalable AI solutions using relevant AI (ML/DL/Gen AI) techniques
• Architects large scale AI solutions that seamlessly merge AI model and techniques in SDLC
• Organizes and leads comprehensive code and design review sessions, driving discussions to align with project requirements and best practices. Mentor and provide feedback to junior and mid-level team members.
• Conducts research and stays up to date with the latest advancements in AI and machine learning technologies, frameworks, and algorithms. Explore and experiment with cutting-edge techniques to solve complex problems and improve existing models.
• Collaborates with cross-functional teams to understand business requirements and design AI and machine learning solutions. Determine the appropriate algorithms, models, and frameworks to use and architect the overall system to ensure scalability, efficiency, and robustness.
• Develops, implements, and optimizes machine learning models and algorithms. This includes data pre-processing, feature engineering, model selection, hyperparameter tuning, and training on large datasets. Continuously monitor and improve model performance and accuracy.
• Leverage or build analytics tools that utilize the data pipeline to provide significant insights into customer case data, bug data, operational and other key business performance metrics.
• Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources
• Work with data and analytics specialists to strive for greater functionality in our data systems.
• Identify trends, patterns from dataset to scope opportunities for automation
• Deploys machine learning models into production environments, considering scalability, performance, and security considerations.
• Integrate models with existing software systems and infrastructure, ensuring smooth operation and interoperability.
• Monitors the performance of deployed models, collects relevant metrics, and analyzes data to identify areas for improvement. Based on insights gained from monitoring and analysis, fine-tune models, optimize algorithms, and enhance system performance.
• Works collaboratively with the engineering manager and team lead to set design and implementation standards, ensuring continuous improvement and alignment with project goals.
• Regularly leads meetings, fostering a collaborative and productive team environment.
• Has experience in providing technical leadership, mentorship, and guidance to junior team members.
• Address and resolve challenges proactively.
• Develops and delivers strategic presentations and reports to senior stakeholders, demonstrating a deep understanding of technical and business aspects. Provide insights and recommendations.
• Applies and leverages data mining, data modeling, natural language processing, and machine learning to extract and analyze information from datasets.

What You Need to Bring:

• We are looking for a candidate with 11+ years of experience in a Data science role, who has attained a Graduate degree in Computer Science, Statistics, Informatics, Information Systems or another quantitative field.
• 6+ years experiences building data pipelines for data science-driven solutions and deployed multiple solutions in Production environment
• In depth knowledge in one or more AI technologies: Classical ML , NLP, Gen AI , Agentic AI , MCP etc.
• Experience working in technical support environment, working with dataset from CRM, H/W and S/W bugs data, machine logs
• Experience supporting and working with multi-functional teams in a multidimensional fast paced environment.
• Good team worker with excellent interpersonal, written, verbal and presentation skills
• Experience building and optimizing data pipelines, architectures and data sets.
• Experience performing root cause analysis on internal and external data and processes to answer specific business questions and find opportunities for improvement.
• Strong analytic skills related to working with unstructured datasets.
• Build processes supporting data transformation, data structures, metadata, dependency and workload management.
• A successful history of manipulating, processing and extracting value from large, disconnected datasets.
• Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
• Strong hands-on coding skills (preferably in Python) processing large-scale data set and developing machine learning model
• A strong foundation in mathematics and statistics. In-depth knowledge of linear algebra, calculus, probability theory, and statistical concepts. Understanding and developing complex machine learning models and algorithms.
• Good knowledge on Software Development Life Cycle ( SDLC ) and Agile principles
• Experience working with Large Language models, Generative AI, Conversational AI
• Familiar with one or more machine learning or statistical modeling tools such as Numpy, ScikitLearn, MLlib, Tensorflow, NLP libraries
• Experience working with Databricks, Snowflake platforms
• Experience with AWS, S3, Spark, Kafka, Elastic Search
• Experience with big data tools: Hadoop, Spark, Kafka, etc.
• Experience with relational SQL and NoSQL databases, including Postgres and Cassandra.
• Experience with data pipeline and workflow management tools

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