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AI Software Ecosystem \- AI Solution Architect and Consultant
Description \-
The Commercial PC Business is a high\-growth, fast\-paced business with an innovation and customer\-centered mindset delivering solutions for our enterprise, mid\-market, and SMB customers. The AI Software Ecosystem team has responsibility for partnering with leading software application vendors as well as startups on AI use cases with the AI PC.
The AI Solutions Architect and Consultant is responsible for consulting with ISVs on technical implementation and ROI of leveraging local models on the device, as well as driving the technology vision for the AI Software Ecosystem team. In this pivotal role, you will leverage your deep technical and business expertise to advise on workloads and use cases best suited for hybrid AI or on\-device AI across cloud and local (CPU, GPU, and NPU). Skills and knowledge in developer tools across silicon partners, full software stack, solutions architecting, business industry knowledge, and technical consulting is needed to influence and consult with software developers enabling growth of a brand new category for AI PCs.
Key Responsibilities
- Consult with third party software developers on technical considerations and developer tools to optimize their local models across silicon providers.
- Work closely with partners and internal R\&D teams on technical differentiation opportunities, determining API and SDK requirements.
- Advise on workloads, models, and use cases collaborating with ISV and HP’s technical, product, and business development teams.
- Provide technical requirements and frameworks to the software development team.
- Define POC requirements and manage POC development team
- Develop content and whitepapers to establish HP leadership for ease of development.
- Stay abreast of evolving AI developer landscape and be established as a subject matter expert.
- Work with ecosystem partners and internal teams on short, medium, and long term differentiation roadmaps for the commercial business.
- Research and anticipate future technology trends and market needs through expert analysis of the computer industry landscape: hardware, software, services, applications, ecosystems, etc. with a vision 3, 5\+ years out.
- Serve as a thought leader, delivering engaging presentations, primers and knowledge sharing to internal and external audiences.
Qualifications
- 10\+ years of experience in the computer/technology industry, including roles in solutions architecture, software development, consulting, business development/sales engineering, product management, and management.
- Entrepreneurial mindset with the drive to continuously innovate and stay ahead of market demands.
- Hybrid AI software development expertise and PC hardware knowledge.
- Strong customer and partner communication skills, as well as the ability to influence CxO level as well as technical R\&D teams.
- Exceptional customer centric skills, understanding of use cases.
- Technical visionary with proven track record in successfully architecting cutting\-edge computing solutions that eventually come to market.
- Exceptional technical depth across PC hardware, HW components, AI models/applications, commercial and consumer software applications, operating systems, silicon platforms, collaboration systems, PC telemetry/analytics, HW/SW ecosystems, and a wide variety of commercial and consumer computing solutions.
- Strong business acumen leveraging best practices with the ability to map technology capabilities to strategic business drivers.
- Provides subject matter expertise and consults to our ISVs and customers establishing HP as a leader, as well as consults to internal HP to support execution of Future of Work principles within HP.
- Builds relationships with other distinguished technologies, fellows, solution architects and futurists pan\-HP.
- Excellent presentation and interpersonal skills to build credibility and distinction with external partners and customers, stakeholders and HP colleagues.
The pay range for this role is $130,700 to $205,200 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 \-
Services
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 "
Salary Context
This $130K-$205K range is below the median for AI/ML Engineer roles in our dataset (median: $180K across 1937 roles with salary data).
View full AI/ML Engineer salary data →Role Details
About This Role
AI/ML Engineers build and deploy machine learning models in production. They work across the full ML lifecycle: data pipelines, model training, evaluation, and serving infrastructure. The role has evolved significantly over the past two years. Where ML Engineers once spent most of their time on model architecture, the job now tilts heavily toward inference optimization, cost management, and integrating LLM capabilities into existing systems. Companies want engineers who can ship production systems, and the experimenter-only role is fading fast.
Day-to-day, you're writing training pipelines, debugging data quality issues, setting up evaluation frameworks, and figuring out why your model performs differently in staging than it did on your dev set. The best ML engineers are obsessive about reproducibility and measurement. They instrument everything. They know that a model is only as good as the data feeding it and the infrastructure serving it.
Across the 3,823 AI roles we're tracking, AI/ML Engineer positions make up 69% of the market. At HP, this role fits into their broader AI and engineering organization.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
What the Work Looks Like
A typical week might include: debugging a data pipeline that's silently dropping 3% of training examples, running A/B tests on a new model version, writing documentation for a feature flag system that lets you roll back model deployments, and reviewing a junior engineer's PR for a new evaluation metric. Meetings tend to be cross-functional since ML touches product, engineering, and data teams.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
Skills in Demand for This Role
Python and PyTorch dominate the requirements. Most roles expect experience with cloud platforms (AWS, GCP, or Azure) and familiarity with ML frameworks like TensorFlow or JAX. RAG (Retrieval-Augmented Generation) has become a top-3 skill requirement as companies integrate LLMs into their products. Docker and Kubernetes show up in about a third of postings, reflecting the production focus of the role.
Beyond the core stack, employers increasingly want experience with experiment tracking tools (MLflow, Weights & Biases), feature stores, and vector databases. Fine-tuning experience is valuable but less common than you'd think from reading Twitter. Most production LLM work is RAG and prompt engineering, not fine-tuning. If you have both, you're in a strong position.
Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
Compensation Benchmarks
AI/ML Engineer roles pay a median of $181,170 based on 12,692 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $165,000. This role's midpoint ($167K) sits 7% below the category median. Disclosed range: $130K to $205K.
Across all AI roles, the market median is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Engineering Manager ($275,000) and AI Safety ($274,200). By seniority level: Entry: $97,880; Mid: $165,000; Senior: $227,400; Director: $247,800; VP: $250,000.
HP AI Hiring
HP has 3 open AI roles right now. They're hiring across AI/ML Engineer. Positions span Fort Collins, CO, US, Spring, TX, US. Compensation range: $143K - $274K.
Location Context
Across all AI roles, 15% (590 positions) offer remote work, while 3,217 require on-site attendance. Top AI hiring metros: New York (2,643 roles, $211,000 median); San Francisco (2,168 roles, $253,000 median); Los Angeles (1,792 roles, $191,580 median).
Career Path
Common paths into AI/ML Engineer roles include Data Scientist, Software Engineer, Research Engineer.
From here, career progression typically leads toward ML Architect, AI Engineering Manager, Principal ML Engineer.
The fastest path into ML engineering is through software engineering with a self-directed ML education. A CS degree helps, but production engineering skills matter more than academic credentials. Build something that works, deploy it, and measure it. That portfolio project is worth more than a Coursera certificate. For career growth, the fork comes around the senior level: go deep on technical complexity (staff/principal track) or move into managing ML teams.
What to Expect in Interviews
Expect system design questions around ML pipelines: how you'd build a training pipeline for a specific use case, handle data drift, or design A/B testing infrastructure for model deployments. Coding rounds typically involve Python, with emphasis on data manipulation (pandas, numpy) and algorithm implementation. Take-home assignments often ask you to build an end-to-end ML pipeline from raw data to deployed model.
When evaluating opportunities: Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
AI Hiring Overview
The AI job market has 3,823 open positions tracked in our dataset. By seniority: 112 entry-level, 1,798 mid-level, 1,516 senior, and 397 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (590 positions). The remaining 3,217 roles require on-site or hybrid attendance.
The market median for AI roles is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. Highest-paying categories: AI Engineering Manager ($275,000 median, 41 roles); AI Safety ($274,200 median, 55 roles); Research Engineer ($260,000 median, 434 roles).
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
The AI Job Market Today
The AI job market spans 3,823 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,629), Data Scientist (322), AI Software Engineer (279). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (112) are outnumbered by mid-level (1,798) and senior (1,516) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 397 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (590 positions), with 3,217 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $200,100. Top-quartile roles start at $253,500, and the 90th percentile reaches $307,500. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Engineering Manager roles lead at $275,000 median, while Prompt Engineer roles sit at $140,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,979 postings), Aws (1,190 postings), Azure (899 postings), Rag (839 postings), Gcp (726 postings), Pytorch (595 postings), Prompt Engineering (595 postings), Claude (540 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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