Experienced AI Engineer for Storage Domain at Hewlett Packard Enterprise

Bengaluru, Karnataka, India

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Not SpecifiedCompensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Technology, Cloud Computing, StorageIndustries

Requirements

Experience leading cross-functional teams in AI solutions for business benefits
Expertise in designing and developing solutions using patterns in petabyte-scale objects and files in distributed enterprise storage platforms
Proficiency in designing, developing, and deploying hybrid RAG architectures integrating LLMs with retrieval-based systems
Skills in functional design, process design (scenario design, flow mapping), prototyping, testing, training, and defining support procedures
Ability to translate technical AI findings into business-oriented language for non-technical stakeholders
Experience implementing and managing pipelines combining retrieval mechanisms with generative capabilities
Knowledge of developing custom plugins, adapters, or APIs to integrate retrieval systems (e.g., Elasticsearch) with generative models
Expertise in fine-tuning and optimizing large language models for domain-specific requirements
Capability to monitor, troubleshoot, and optimize pipelines, retrieval parameters, and model hyperparameters
Experience evaluating and benchmarking vector databases and integrating vector search into production systems
Skills in evaluating and benchmarking solution performance using metrics like response accuracy, latency, and user satisfaction
Ability to articulate, document solutions architecture, and lessons learned
Experience serving as liaison between stakeholders and project teams
Proficiency in demonstrating innovative AI use-cases, conducting workshops, training sessions, and technical papers

Responsibilities

Lead cross-functional teams in identifying and prioritizing key areas of a partner’s business where AI solutions can drive significant business benefit
Design and develop solutions leveraging patterns in the data and metadata stored in Petabytes of Objects and Files in distributed fashion across enterprise storage platform
Design, develop, and deploy hybrid RAG architectures integrating LLMs with retrieval-based systems for improved relevance and contextual responses
Work on functional design, process design (including scenario design, flow mapping), prototyping, testing, training, and defining support procedures, in collaboration with an advanced engineering team and executive leadership
Translate technical AI findings into clear, business-oriented language for non-technical stakeholders to support AI-driven business strategies
Implement and manage pipelines that effectively combine retrieval mechanisms with generative capabilities, ensuring high accuracy and efficiency
Develop custom plugins, adapters, or APIs to integrate retrieval systems (e.g., Elasticsearch) with generative models, facilitating seamless information retrieval
Fine-tune and optimize large language models, enhancing their performance and adaptability to domain-specific requirements
Monitor and troubleshoot issues within pipelines, fine-tuning retrieval parameters and model hyperparameters to optimize performance
Evaluate and benchmark the performance of vector databases and collaborate with data scientists and software engineers to integrate vector search capabilities into production systems
Evaluate and benchmark the performance of solutions, using metrics such as response accuracy, latency, and user satisfaction
Articulate and document the solutions architecture and lessons learned for each exploration and accelerated incubation
Serve as liaison between stakeholders and project teams, delivering feedback and enabling team members to make necessary changes in product performance or presentation
Demonstrate innovative AI use-cases, conducting workshops and training sessions, technical paper and presentations

Skills

Key technologies and capabilities for this role

AIMachine LearningObject StorageStorage SystemsData IntelligenceCloud PlatformsHPE GreenLakeCross-functional Leadership

Questions & Answers

Common questions about this position

Is this a remote or hybrid role?

This role is designed as ‘Hybrid’ with an expectation to work on average 2 days per week from an HPE office.

What is the salary or compensation for this position?

This information is not specified in the job description.

What key skills are required for this AI Engineer role?

The role requires experience leading cross-functional teams for AI solutions, designing hybrid RAG architectures integrating LLMs with retrieval systems, developing pipelines combining retrieval and generative capabilities, and working with data and metadata in petabytes of objects and files across enterprise storage.

What is the company culture like at HPE?

HPE's culture thrives on finding new and better ways to accelerate what’s next, values varied backgrounds, offers flexibility to manage work and personal needs, embraces bold moves together, and supports career growth.

What makes a strong candidate for this Experienced AI Engineer position?

Strong candidates will have experience leading cross-functional teams, designing AI solutions for enterprise storage like HPE Alletra Storage MP X10000, developing hybrid RAG architectures with LLMs, and translating technical AI findings into business language.

Hewlett Packard Enterprise

Provides enterprise IT solutions and services

About Hewlett Packard Enterprise

Hewlett Packard Enterprise provides enterprise IT solutions with a focus on cloud services, artificial intelligence, and edge computing. Their products include HPE Ezmeral for managing containers, HPE GreenLake for cloud services, and HPE Aruba for networking. These solutions help businesses improve their performance and adapt to digital changes. HPE's business model includes selling hardware, software, and services, as well as offering subscription-based services and long-term contracts. What sets HPE apart from competitors is its commitment to open-source projects and its active developer community, which supports collaboration and innovation. The company's goal is to empower organizations to transform digitally and optimize their operations.

Houston, TexasHeadquarters

1939Year Founded

IPOCompany Stage

Hardware, Enterprise Software, AI & Machine LearningIndustries

10,001+Employees

Risks

Integration challenges with Juniper Networks may delay AI-driven networking benefits.

Competition from startups like Flywheel could impact HPE's AI and cloud services.

HPE's acquisition strategy may strain resources and distract from core operations.

Differentiation

HPE's GreenLake offers a unique hybrid cloud platform for diverse IT environments.

HPE Ezmeral provides advanced container management, enhancing enterprise AI and analytics capabilities.

HPE's Aruba solutions integrate cloud security and networking for seamless, secure connectivity.

Upsides

HPE's acquisition of Juniper Networks boosts AI-driven innovation in networking.

OpsRamp acquisition enhances HPE's IT management with AI-based automation capabilities.

Axis Security integration strengthens HPE's cloud security offerings with SASE solutions.

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