Distinguished Technologist – Director, AI Strategy and Enablement

Hewlett Packard Enterprise

. Define and drive the enterprise AI enablement strategy and roadmap for OCTO and HPE Labs, aligned to HPE business priorities.

Posted 5/20/2026full-timeMilpitas • California, Colorado, Texas • 🇺🇸 United StatesLead💰 $179,500 - $412,500 per yearWebsite

Tech Stack

Tools & technologies

AWSAzureCloudOpenStackVMware

About the role

Key responsibilities & impact

Define and drive the enterprise AI enablement strategy and roadmap for OCTO and HPE Labs, aligned to HPE business priorities.
Act as a hands on Distinguished Technologist: set architecture, patterns, and best practices for AI/ML systems; contribute to prototypes and complex implementations; and validate designs for scale, resilience, and security.
Lead research transition: collaborate with HPE Labs to mature innovations into production-ready components and repeatable delivery patterns.
Establish and enforce governance: model validation and evaluation standards, ethical/ responsible AI guardrails, data privacy/compliance, and risk management practices across AI initiatives.
Build, mentor, and grow a high performing team of applied AI engineers and data scientists; nurture technical leadership and cross functional collaboration.
Partner broadly across product, engineering, security, legal, data engineering, and field teams to operationalize AI use cases and maximize reuse across HPE.
Measure and communicate impact: define KPIs for adoption, ROI, model performance, reliability, and operational cost; report progress to OCTO, HPE Labs and senior leadership.
Represent HPE externally: engage customers, partners and the technical community to evangelize HPE’s AI enablement approach and gather field feedback that shapes the roadmap.

Requirements

What you’ll need

15+ years of relevant industry experience spanning AI/ML, software engineering, cloud/hybrid infrastructure, and enterprise product delivery
Advanced degree (MS/PhD preferred) in Computer Science, Engineering, Data Science, or related field, or equivalent experience
Deep expertise in modern AI: large language models, generative AI, deep learning, applied machine learning, and production model lifecycle management
Proven track record architecting and delivering mission critical, distributed AI applications and platforms at enterprise scale
Strong background in MLOps, data pipelines, data engineering, model governance, security-by-design, and cloud/hybrid deployment models (OpenStack, AWS, Azure, VMware, GreenLake)
Demonstrated ability to lead cross functional, globally distributed teams and to influence senior stakeholders and executives
Excellent systems design, problem solving, and architectural judgment; familiarity with domain driven, component based and evolutionary architecture approaches.

Benefits

Comp & perks

Health & Wellbeing
Personal & Professional Development
Unconditional Inclusion

ATS Keywords

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Hard Skills & Tools

AI enablement strategymachine learningdeep learningMLOpsdata engineeringmodel governancecloud deployment modelsdistributed AI applicationsproduction model lifecycle managementsystems design

Soft Skills

leadershipcollaborationinfluencementoringcommunicationproblem solvingarchitectural judgmentcross functional teamworkstakeholder engagementgovernance enforcement

Certifications

MS in Computer SciencePhD in Computer ScienceData Science degree