Accelerated Computing Portfolio Lead – AI & HPC Services

MaxIT Consulting - Max Corporate Group; Massachusetts; On-site; USD 180,000 - 260,000; Full time

Benefits offered by this job

Healthcare benefits

401(k) plan

Annual bonus

Equity awards

Employee Stock Purchase Plan

Paid holidays and PTO

Sick leave

Parental benefits

Employee assistance programs

Wellness resources

Job summary

MaxIT Consulting — Max Corporate Group is seeking an Accelerated Computing Portfolio Lead to steer GPU cloud products and services for AI, HPC, graphics, and enterprise workloads. You will translate complex workload requirements into scalable cloud offerings with strong business value.

Responsibilities include defining strategy and roadmaps, building financial models and pricing, and coordinating with sales, solutions engineering, and partners to accelerate adoption while ensuring platform

Qualifications

• . 12 years of relevant experience in Product Management, Technology, Engineering, or a related field.
• . Bachelor's degree in Computer Science, Engineering, or equivalent professional experience.
• . Strong technical understanding of GPU architectures, CUDA, and accelerated computing platforms.
• . Experience with GPU resource management and cluster orchestration for AI and HPC workloads.
• . Knowledge of cloud networking, GPU interconnects, redundancy, and large-scale GPU deployments.
• . Experience developing technical and business models for GPU or cloud products, including pricing, profitability, and TCO analysis.
• . Understanding of AI workloads, enterprise security requirements, and hardware-level APIs related to GPU infrastructure.
• . Proven ability to collaborate with highly technical engineering and data science teams.
• . Strong product strategy, stakeholder management, and communication skills.
• . Ability to balance complex technical requirements with customer needs and business objectives.

Responsibilities

• Define the product strategy, vision, and roadmap for GPU instances, clusters, and cloud services.
• Align product requirements, positioning, and priorities with customer needs, market trends, and business objectives.
• Own the full product lifecycle, from initial planning and launch through optimization and end-of-life.
• Develop business cases, pricing strategies, profitability analyses, and Total Cost of Ownership models.
• Develop and execute go-to-market strategies in partnership with sales, marketing, solutions engineering, and technical teams.
• Collaborate with GPU technology and ecosystem partners to align product roadmaps, integrations, and technical requirements.
• Translate AI, HPC, graphics, and accelerated-computing workloads into product specifications, performance requirements, and infrastructure architectures.
• Guide the evolution of GPU infrastructure and support data-driven decisions regarding platform investments and lifecycle management.
• Identify opportunities to improve automation, usability, monitoring, support, and operational efficiency for GPU workloads.
• Build strong alignment with engineering and data science teams around product goals, technical requirements, and future platform capabilities.

Skills

GPU architectures

CUDA

Accelerated computing

GPU mgmt

Cluster orchestration

Cloud networking

Pricing & profitability

AI workloads

Security requirements

Stakeholder mgmt

Education

Bachelor's degree in CS/Engineering

Job description

Accelerated Computing Portfolio Lead — AI & HPC Services

Remote — United States | Full-Time | Direct Hire

MaxIT Consulting — Max Corporate Group is seeking an experienced Accelerated Computing Portfolio Lead — AI & HPC Services for a leading global technology organization.

This role will lead the strategy, development, and lifecycle management of next-generation GPU cloud products and services supporting AI, high-performance computing, graphics, accelerated computing, and enterprise workloads.

The ideal candidate combines strong product leadership with deep technical knowledge of GPU infrastructure and the ability to translate complex workload requirements into scalable cloud products and sound business decisions.

What You’ll Do

• Define the product strategy, vision, and roadmap for GPU instances, clusters, and cloud services.
• Align product requirements, positioning, and priorities with customer needs, market trends, and business objectives.
• Own the full product lifecycle, from initial planning and launch through optimization and end-of-life.
• Develop business cases, financial models, pricing strategies, profitability analyses, and Total Cost of Ownership models.
• Develop and execute go-to-market strategies in partnership with sales, marketing, solutions engineering, and technical teams.
• Collaborate with GPU technology and ecosystem partners to align product roadmaps, integrations, and technical requirements.
• Translate AI, HPC, graphics, and accelerated-computing workloads into product specifications, performance requirements, and infrastructure architectures.
• Guide the evolution of GPU infrastructure and support data-driven decisions regarding platform investments and lifecycle management.
• Identify opportunities to improve automation, usability, monitoring, support, and operational efficiency for GPU workloads.
• Build strong alignment with engineering and data science teams around product goals, technical requirements, and future platform capabilities.

Required Qualifications

• 12 years of relevant experience in Product Management, Technology, Engineering, or a closely related field.
• Bachelor’s degree in Computer Science, Engineering, or equivalent professional experience.
• Strong technical understanding of GPU architectures, CUDA, and accelerated computing platforms.
• Experience with GPU resource management and cluster orchestration for AI and high-performance computing workloads.
• Knowledge of cloud networking, GPU interconnects, infrastructure redundancy, and large-scale GPU deployments.
• Experience developing technical and business models for GPU or cloud products, including pricing, profitability, and TCO analysis.
• Understanding of AI workload patterns, enterprise security requirements, and hardware-level APIs related to GPU infrastructure.
• Proven ability to collaborate with highly technical engineering and data science teams.
• Strong product strategy, stakeholder management, and communication skills.
• Ability to balance complex technical requirements with customer needs and business objectives.

Ideal Background

Strong candidates may come from environments involving:

• GPU cloud products and services
• AI infrastructure
• High-Performance Computing
• Accelerated computing platforms
• Cloud infrastructure
• GPU cluster orchestration
• Compute platforms
• Large-scale distributed infrastructure
• Enterprise or hyperscale technology environments

Experience taking a GPU, AI infrastructure, or accelerated-computing product from strategy and roadmap through launch and ongoing optimization will be especially valuable.

What Success Looks Like

The successful candidate will be able to demonstrate ownership of at least one GPU, cloud compute, AI infrastructure, or accelerated-computing product or platform.

Relevant accomplishments may include:

• Launching GPU instances, clusters, or cloud services
• Defining GPU infrastructure roadmaps
• Supporting AI or HPC workloads at scale
• Improving GPU utilization or platform efficiency
• Developing pricing, TCO, or profitability models
• Driving customer adoption and product growth
• Coordinating engineering, commercial, and technology partner roadmaps

Benefits

The benefits package may include:

• Healthcare benefits
• 401(k) savings plan
• Annual bonus or incentive opportunities
• Equity awards
• Employee Stock Purchase Plan
• Paid holidays and PTO
• Sick leave
• Parental and family-friendly benefits
• Employee assistance programs
• Mental and financial wellness resources

Work Location and Authorization

This position is remote within the United States.

Candidates must be legally authorized to work in the United States for any employer.

Visa sponsorship is not available for this position, now or in the future.

Relocation is not required.

Interview Process

The selection process is expected to include:

• Technical interview with the Hiring Manager
• Technical panel interviews with discipline and technical leads
• Final non-technical interview with Operations

Candidates should be comfortable working with distributed teams and stakeholders across multiple U.S. and international time zones.