Principal Product Manager, Edge AI, LLM & Agentic Workflows

Hewlett Packard Co.

Palo Alto (CA)

On-site

USD 147,000 - 231,000

Full time

6 days ago
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Benefits offered by this job

Health insurance
Dental insurance
Vision insurance
Disability insurance – long & short
Employee assistance program
Flexible spending account
Life insurance
Parental leave (4–12 weeks) and paid/b
Holidays and flexible time off

Job summary

Hewlett Packard Co. is seeking a Principal Product Manager for Edge AI, LLM and agentic workflows in Palo Alto, CA.

You will own the vision, roadmap, and delivery of inference software for enterprise-scale AI workloads, collaborating with engineering, hardware, services, and ecosystem partners to ensure reliable, scalable solutions. The role emphasizes customer discovery, governance, and deployment validation, translating business needs into robust product requirements and lifecycle management

Qualifications

  • 10+ years of product management for enterprise software or AI products.
  • Experience delivering LLM-enabled applications and inference solutions.
  • Experience defining deployment requirements for model lifecycle, monitoring and updates.
  • Understanding of local, on-prem and hybrid deployment constraints.
  • Fluency with Python-based AI ecosystems, APIs, and developer tooling.
  • Ability to influence cross-functional teams and communicate with technical and executive audiences.

Responsibilities

  • Define product vision, strategy and roadmap for assigned LLM and agentic inference capabilities.
  • Coordinate with engineering, hardware, services, and ecosystem partners to deliver integrated solutions.
  • Translate customer needs into capabilities for deployment and operations across on‑prem and cloud.
  • Define requirements for model serving, governance, and lifecycle management.
  • Drive pilots to production deployments with measurable adoption and business value.
  • Collaborate with GTM and sales to define target customers and packaging decisions.

Skills

Product management
AI software
Model serving
Agent orchestration
Python ecosystems
Stakeholder communication

Education

Bachelor’s degree in CS/Engineering

Tools

Python APIs/SDKs
Open-source AI ecosystems

Job description

Principal Product Manager, Edge AI, LLM & Agentic WorkflowsWe use cookies (or similar technologies) to personalize content and ads, to provide social media features and to analyse our traffic. By clicking \"Accept \", you agree to this and the sharing of information (What data we collect) about your use of our site with our affiliates & partners. Please find out more about Use of cookies.### Principal Product Manager, Edge AI, LLM & Agentic WorkflowsApply: Palo Alto, California, United States of America: Full time: Posted Today: 3170139Principal Product Manager, Edge AI, LLM & Agentic Workflows**Description -****Role Overview** The Principal Product Manager defines product strategy and drives delivery of Edge AI solutions for large language models (LLMs) and agentic workflows, including the inference software capabilities needed to deploy, orchestrate, and operate these workloads in enterprise environments. Within HP’s Edge & AI solutions organization, this role owns the vision, roadmap, requirements, and product outcomes for assigned LLM and agentic inference capabilities. You will partner with engineering, peer product managers, hardware teams, services teams, and ecosystem partners to deliver integrated solutions. The role defines workload requirements and evaluates deployment trade-offs with hardware partners but does not own hardware products or hardware roadmaps. The role combines strategic product leadership with practical execution through customer discovery, technical requirements, prioritization, and deployment validation. You will translate internal and external customer needs into capabilities that help organizations deploy, manage, and scale AI closer to their users, operations, and data. **Key responsibilities:** **Product Strategy & Customer Discovery*** Define the product vision, strategy, and roadmap for assigned LLM and agentic inference capabilities, aligned with HP’s broader Edge AI strategy. Coordinate shared capabilities and dependencies with peer product managers.* Use customer discovery, market insights, competitive analysis, and business cases to prioritize enterprise opportunities for LLM applications, AI agents, and workflow automation.* Validate customer needs, target users, deployment requirements, and expected business value before committing to solution investments. **Solutions Definition*** Define software capabilities and integration requirements for LLM and agentic inference solutions across local, on-premises, and hybrid environments. Partner with hardware and services owners to ensure the overall solution meets workload and customer requirements.* Establish requirements for model serving and assigned inference software stack capabilities, including deployment, runtime compatibility, scaling, support for relevant inference backends, and integration with HP Z Runtime where applicable. Work with engineering and hardware partners to evaluate workload requirements and trade-offs across compute, memory, acceleration, connectivity, performance, and cost.* Define requirements for agent orchestration, tool use, enterprise system integration, human oversight, and recovery from failed or incomplete tasks.* Translate model lifecycle, security, privacy, and governance needs into product requirements, including evaluation, deployment, monitoring, versioning, updates, rollback, access controls, and auditability. **Delivery & Ecosystem Partnerships*** Partner with peer product managers, engineering, and operations to translate the roadmap into prioritized requirements, acceptance criteria, and coordinated delivery plans.* Engage internal and external customers, independent software vendors (ISVs), and ecosystem partners to validate LLM and agentic workflows and guide pilots toward reliable, supportable production deployments. Use relevant Customer Zero initiatives as one source of deployment evidence and product feedback.* Evaluate build, buy, and partner options across the solution stack, establishing clear integration requirements and responsibilities with relevant teams. **Go-to-Market & Product Outcomes*** Partner with product marketing and sales to define target customers, articulate differentiated value, inform pricing and packaging decisions, and develop launch plans and sales enablement materials.* Define and track adoption, time to production, workflow effectiveness, reliability, usability, and customer value.* Use customer feedback and product performance evidence to refine priorities and improve the solution throughout its lifecycle. **Core Outputs & Artifacts*** **Product Strategy and Roadmap:** A clear view of target customers, priority LLM and agentic workflows, differentiated value, and planned inference software capabilities, including dependencies on shared components, hardware, services, and partners.* **Prioritized Product Requirements:** Requirements and acceptance criteria covering assigned inference software capabilities, enterprise controls, integration interfaces, and deployment needs, with workload requirements communicated to hardware and services owners.* **Validated Customer and Deployment Findings:** Evidence from discovery, pilots, and production use that informs product decisions, including success criteria and barriers to adoption.* **Launch and Production Readiness Inputs:** Product inputs covering integration dependencies, deployment and support requirements, partner responsibilities, positioning, and measures of success. **What Success Looks Like*** A focused roadmap connects enterprise customer needs with HP’s Edge AI strategy and integrated solution capabilities.* Customers move from AI experimentation and pilots into production deployments with clear operational and business value.* Assigned inference software capabilities enable reliable, manageable LLM applications and agentic workflows in the intended deployment environments.* Engineering, Go-to-Market, operations, and ecosystem partners share clear priorities, acceptance criteria, and delivery responsibilities.* Product decisions are informed by adoption, customer feedback, task success, reliability, inference latency, and deployment cost, using measures appropriate to each solution. **Experience knowledge & skills:** **Required*** 10+ years of relevant experience, including substantial product management responsibility for enterprise software, AI software, developer tools, or infrastructure products, with demonstrated ownership of strategy, roadmaps, and delivery.* Demonstrated experience delivering LLM-enabled applications or inference solutions, with technical fluency in model serving, retrieval-augmented generation, agent orchestration, tool use, evaluation, and failure handling.* Experience defining requirements for model deployment and lifecycle management, including monitoring, versioning, updates, and supportability in enterprise environments.* Understanding of local, on-premises, and hybrid deployment constraints, with the ability to translate workload needs into requirements for engineering and hardware partners.* Working fluency with Python-based AI ecosystems, APIs, SDKs, and developer tooling, sufficient to evaluate integration and deployment approaches alongside engineering.* Experience translating enterprise integration, security, privacy, and governance needs into product requirements.* Experience collaborating with technology partners and peer product managers to deliver integrated solutions and manage shared dependencies.* Strong analytical judgment and experience using customer feedback, deployment findings, and performance evidence to prioritize product improvements.* Demonstrated ability to influence cross-functional teams without direct authority, communicate with technical and executive audiences, and translate strategy into prioritized requirements and acceptance criteria. **Preferred*** Experience evaluating build, buy, and partner options for enterprise platforms or integrated technology solutions.* Experience with open-source AI ecosystems and enterprise model-serving or agent-orchestration platforms.* Experience supporting product positioning, pricing and packaging decisions, and Go-to-Market execution for enterprise technology offerings. **Education:*** Bachelor’s degree in Computer Science, Engineering, Data Science, or a related field, or equivalent relevant professional experience.* An MBA or an advanced degree in a relevant technical field is a plus but not required. **Disclaimer** • This job description describes the general nature and level of work performed in this role. It is not intended to be an exhaustive list of all duties, skills, responsibilities, knowledge, etc. These may be subject to change and additional functions may be assigned as needed by management. **Salary** The pay range for this role is **$147,050** to **$230,850** USD annually with additional opportunities for pay in the form of bonus and/or equity (applies to United States of America candidates only). Pay varies by work location, job-related knowledge, skills, and experience. **Benefits:** HP offers a comprehensive benefits package for this position, including:* Health insurance* Dental insurance* Vision insurance* Long term/short term disability insurance* Employee assistance program* Flexible spending account* Life insurance* Generous time off policies, including;* 4-12 weeks fully paid parental leave based on tenure* 11 paid holidays* Additional flexible paid vacation and sick leave (US benefits overview)The compensation and benefits information is accurate as of the date of this posting. The Company reserves the right to modify this information at any time, with or without notice, subject to applicable law.**Job -**Software**Schedule -**Full time**Shift -**No shift premium (United States of America)**Travel -****Relocation -****Equal Opportunity Employer (EEO) -**HP, Inc. provides equal employment opportunity to all employees and prospective employees, without regard to race, color, religion, sex, national origin, ancestry, citizenship, sexual orientation, age, disability, or status as a protected veteran, marital status, familial status, physical or mental disability, medical condition, pregnancy, genetic predisposition or carrier status, uniformed service status, political affiliation or any other characteristic protected by applicable national, federal, state, and local law(s).Please be assured that you will not be subject to any adverse treatment if you choose to disclose the information requested. This information is provided voluntarily. The information obtained will be kept in strict confidence.For more information, review HP’s EEO Policy or read about your rights as an applicant under the law here: “Know Your Rights: Workplace Discrimination is Illegal\"
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