AI & Analytics Workload Specialist, Hewlett Packard Enterprise

Hewlett Packard Enterprise

Location:
India, Bangalore

Category:
IT - Software Development

Contract Type:
Employment contract

Salary:

Not provided

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Job Description:

The HPE Worldwide Hybrid Cloud Acceleration Team is seeking a technically skilled and innovative Solutions Engineer to join their AI and Analytics team. In this role, you will work on designing and validating workload solutions, creating technical assets, and supporting field enablement. This is a full-time onsite position based in Bangalore, India.

Job Responsibility:

apply technical expertise to design and validate AI/Analytics workload solutions
contribute technical assets such as demos, white papers, videos, blogs, labs, and internal enablement materials
collaborate with stakeholders to define the scope and align solutions with business needs
leverage internal infrastructure and AI-powered tools to accelerate development and validation
create compelling enablement content for the field, partners, and customers
support solution adoption through TekTalks, webinars, Slack forums, and internal events
integrate assets with field tools and help measure asset utilization
invest in technical and personal growth through internal training, certifications, mentorships, and participation in HPE’s Technical Career Path (TCP)
contribute to team goals, mentor peers, and participate in a collaborative engineering environment.

Requirements:

2 - 4 years of hands-on experience in building or validating AI and Analytics solutions, with a focus on real-world enterprise use cases
proven experience developing or deploying AI-powered applications such as Retrieval-Augmented Generation (RAG) systems, conversational AI/chatbot solutions, ML model pipelines for analytics or inference
strong proficiency in Python and familiarity with common AI/ML frameworks (e.g., LangChain, Hugging Face, PyTorch, TensorFlow, OpenAI APIs)
hands-on experience with data manipulation, embedding/vector databases (e.g., FAISS, Chroma, Weaviate), and prompt engineering
experience with virtualization platforms (e.g., VMware, KVM) and containers (e.g., Docker, Kubernetes) is a plus
familiarity with deploying AI workloads in cloud environments (e.g., Azure, AWS, or GCP), particularly using GPU-accelerated instances, is a plus
strong written and verbal communication skills, with the ability to explain complex technical ideas clearly
bachelor’s degree in computer science, Data Science, Engineering, or a related technical field.

Nice to have:

understanding of enterprise IT systems, storage, and hybrid cloud architecture
prior experience building AI/ML solution reference architectures or benchmarks
published technical content (e.g., blogs, demos, white papers).

What we offer:

health and wellbeing benefits
personal and professional development programs
inclusive workplace environment.

Additional Information:

Job Posted:
July 18, 2025

Employment Type:

Fulltime

Work Type:

On-site work

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AI & Analytics Workload Specialist