OpenAIRemote · San Francisco$401k-$536kjust now
Hewlett Packard EnterprisePosted today
Distinguished Technologist, AI Value Architect - Private Cloud AI at Hewlett Packard Enterprise scores 76 out of 100 on AI centrality, which makes it AI Level 3 of 4 (Works on AI) on this board. The level measures how much of the work is AI, not seniority.
AI in this role
This role has been designed as 'Hybrid' with a requirement that you will work on average 2 days per week 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:
As an AI Value Architect for Central Europe, you will own the Day-2 value, adoption and expansion lifecycle for a portfolio of strategic HPE Private Cloud AI customers. You will act as a trusted technical advisor and AI value partner after initial deployment, helping customers turn early onboarding outcomes into broader internal adoption, stronger champions, clearer AI roadmaps and measurable business impact. You will combine deep technical credibility in enterprise AI and Generative AI with confident, commercial judgment: identifying where customers are stuck, what they need next, and where additional Private Cloud AI capacity, capabilities or services create the next step in their AI journey.
You will be Geo-aligned and customer-present while operating as part of a globally coordinated team. This is a customer-facing technical sales role, not a delivery or consulting role: you will help customers understand what is possible with Private Cloud AI, review progress against their roadmap, uncover blockers, identify new internal use cases and champions, and work closely with Sales, Pre-Sales, Forward Deployed Engineering, Product and Support to turn validated needs into clear next steps.
What You’ll Do:
Continuous Value Creation
- Own a portfolio of strategic Private Cloud AI customers beyond initial onboarding and drive continued internal adoption, value realization and expansion of Private Cloud AI across business units.
- Discover and shape new AI, GenAI and agentic AI use cases across business units, moving customers from initial workloads to broader production adoption.
- Provide architecture guidance for new workloads across inference, RAG, AI agents, model serving, fine-tuning, data pipelines, observability, governance and security.
- Evangelize Private Cloud AI inside the customer organization by enabling technical and business champions, sharing relevant roadmap updates, and helping teams understand where Private Cloud AI can support their next AI initiatives.
Structured Adoption Cadence
- Establish a programmatic customer cadence with quarterly value, adoption and roadmap reviews involving customer stakeholders and relevant HPE account teams.
- Run outcome-focused business and technical reviews that ask practical adoption questions: what was achieved since onboarding, how much of the roadmap has progressed, where the customer is stuck, what blockers exist, and what technical or commercial actions are needed next.
- Plan and lead regular onsite engagements at strategic customers; travel frequently within Central Europe as a core part of the role and selectively worldwide.
- Maintain clear account plans, actions, risks, value hypotheses and expansion signals across the portfolio.
Expansion & Proof
- Identify, qualify and technically shape expansion opportunities by recognizing where customers need additional Private Cloud AI capacity, new capabilities, platform expansion or related services to execute their AI roadmap.
- Run targeted roadmap, architecture, scaling and adoption workshops when expansion triggers emerge, focused on clarifying the customer’s next AI priorities and required Private Cloud AI capabilities.
- Build the technical and commercial value case for expansion, connect it to roadmap progress and measurable outcomes, and hand validated opportunities to Sales with clear scope, customer evidence and next-step recommendations.
- Partner with local Sales, Pre-Sales and Partners through opportunity progression while remaining a trusted technical and commercial advisor who is comfortable discussing investment needs, expansion options and customer outcomes.
Build the Global Playbook
- Design customer workshops, discovery guides, assessment tools, reference architectures and proof patterns that can be reused across customer sites and GEOs.
- Create the operating model, templates, metrics and governance for a new global AI value and expansion motion.
- Capture field learnings, customer roadmap signals, adoption blockers and expansion patterns, feed them back to Product and global teams, and continuously improve the playbook.
- Operate effectively in a build-from-scratch, startup-style environment with high ownership, ambiguity and pace.
How Success Will Be Measured:
- Expansion creation: qualified, sales-accepted opportunities for additional Private Cloud AI systems and related services.
- Program scale: reusable workshops, assets and operating practices adopted across the global team.
- Customer trust: sustained executive and practitioner engagement with strategic accounts.
- Customer value: additional use cases activated, stronger internal champions, measurable roadmap progress, broader adoption across business units, stronger customer self-sufficiency and increased platform utilization.
What You Need to Bring:
Technical Requirements
- 15+ years of experience in customer-facing roles, with proven ownership of the technical design and architecture of enterprise solutions
- Must have strong hands-on expertise across enterprise AI and GenAI architectures, including LLM inference, RAG, vector databases, AI agents, model endpoints, evaluation, guardrails and LLMOps/MLOps.
- Familiarity and first experiences with agent harness such as OpenClaw, NemoClaw, Hermes and OpenCode.
- Experience designing or implementing production AI solutions using Python, Linux, containers, Kubernetes, Helm, APIs, identity and access controls, and object/file storage.
- Knowledge of data engineering and ML platforms such as Airflow, Kubeflow, MLflow, Ray, model serving frameworks and observability tooling.
- Working knowledge around GPUs, Power Cooling and Networking.
- Ability to reason end-to-end - from customer outcome and data readiness through application architecture, platform sizing, security, operations and scale.
- Experience with NVIDIA AI Enterprise technologies, HPE Private Cloud AI, or comparable enterprise AI platforms is strongly preferred.
Customer & Commercial Skills
- Demonstrated success in a customer-facing technical sales or advisory role such as AI Solutions Architect, Value Architect, Pre-Sales Engineer, Forward Deployed Engineer, Customer Engineer or Field CTO-style role.
- Ability to translate complex AI technology into business value, facilitate workshops with technical and executive stakeholders, and influence without direct authority.
- Strong commercial curiosity and judgment: able to recognize expansion signals, ask direct investment-oriented questions, build a credible technical value case and collaborate with Sales without compromising trusted-advisor status.
- Strong program and account management skills across multiple strategic customers, with disciplined follow-through and concise executive communication.
- Excellent written and verbal communication skills in English; additional European languages are an advantage.
Ways of Working
- Builder mentality: comfortable creating a new motion, assets and processes rather than inheriting a mature playbook.
- High ownership, bias for action and comfort operating in ambiguity.
- Collaborative and low-ego, with the ability to work across GEO and global teams.
- Willingness and ability to travel frequently for onsite customer engagements across Central Europe, with occasional international travel.
Part-time work or job-sharing is also applicable to this position.
Accessibility
HPE is committed to creating an inclusive and accessible workplace and encourages applications from all qualified individuals, including those with disabilities. If you believe you require accommodation during any stage of the application or interview process, please submit your request by completing our secure form linked here.
Note: This option is reserved for applicants needing assistance/reasonable accommodation related to a disability.
What We Can Offer You:
Health & Wellbeing
We strive to provide our team members and their loved ones with a comprehensive suite of benefits that supports their physical, financial and emotional wellbeing.
Personal & Professional Development
We also invest in your career because the better you are, the better we all are. We have specific programs catered to helping you reach any career goals you have — whether you want to become a knowledge expert in your field or apply your skills to another division.
Unconditional Inclusion
We are unconditionally inclusive in the way we work and celebrate individual uniqueness. 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.
Let's Stay Connected:
Follow @HPECareers on Instagram to see the latest on people, culture and tech at HPE.
#germany#hybridcloud, #salesJob:
SalesJob Level:
TCP_07
HPE is an Equal Employment Opportunity/ Veterans/Disabled/LGBT employer. We do not discriminate on the basis of race, gender, or any other protected category, and all decisions we make are made on the basis of qualifications, merit, and business need. Our goal is to be one global team that is representative of our customers, in an inclusive environment where we can continue to innovate and grow together. Please click here: Equal Employment Opportunity.
Hewlett Packard Enterprise is EEO Protected Veteran/ Individual with Disabilities.
HPE will comply with all applicable laws related to employer use of arrest and conviction records, including laws requiring employers to consider for employment qualified applicants with criminal histories.
Recruitment Fraud Alert
We have become aware of an increase in fraudulent recruitment activities in which individuals impersonate our company or authorized recruitment agencies to offer fake employment opportunities. These scams may occur through false websites, emails, social media, or chat-based applications and often aim to obtain personal information or money. Please note that Hewlett Packard Enterprise (HPE), its direct and indirect subsidiaries and affiliated companies, and its authorized recruitment agencies/vendors will never charge a candidate a registration fee, hiring fee, or any other fee in connection with its recruitment and hiring process. We also never request personal information such as back account details, Social Security numbers, or national IDs via social media or chat applications.
All legitimate job opportunities will come through official company channels, and candidates are responsible for verifying the credentials of any third party claiming to represent the company. Any reliance on fraudulent communication is at the individual’s own risk, and HPE disclaims legal liability for any resulting damages. If you suspect recruitment fraud, do not share personal information or make any payments and report the incident to your local authorities immediately.
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Skills and AI tools this role asks for
Questions you could be asked
- How would you design a retrieval step so the model answers from real data instead of guessing?
- How do you decide when an AI agent can act on its own versus asking for approval first?
- Walk me through fine-tuning a model: what data did you use, and how did you check the result?
- How do you monitor a model once it's live, and how do you know it needs retraining?
- Walk me through how you've used Mlflow in your day-to-day work.
Adapt your resume
- List these exact terms on your resume: Rag, AI Agents, Fine Tuning, Ml Ops, and Mlflow. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
- Show where AI is part of your daily process, not a one-off project — this role expects it to be a running habit.
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