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# Account CTO

Review the role, location requirements, compensation details, and application process before deciding whether this opportunity fits your next career move.

[Apply for this job](#job-application)[View company](https://jobicy.com/company/lambda.md)Share6 Sep 2026Published26Listing views2Application actions6 Oct 2026Apply before  Opportunity details

## About this role.

AI SummaryLambda is hiring an Account CTO to serve as the senior technical and business advisor for strategic AI cloud accounts. The role combines enterprise cloud architecture, AI/ML infrastructure expertise, executive relationship management, and strategic account expansion. This leader will guide multi-year customer roadmaps, lead architecture and value assessments, manage critical technical escalations, and influence Lambda’s product strategy. Candidates need extensive experience with large-scale GPU clusters, NVIDIA platforms, high-performance storage and networking, and enterprise AI transformation. The position also requires credible C-suite and board-level communication, thought leadership, and the ability to align technical strategy with major commercial outcomes.

## Role DNA

A quick view of the complexity, pace, ownership and collaboration implied by the job description.

### Job Complexity

5/5EasyHard

### Pace & Pressure

5/5RelaxedFast-paced

### Autonomy Level

5/5GuidedFull ownership

### Communication Load

5/5IndependentCollaborative

AI insightThis is a highly senior, externally facing technical leadership role requiring 15+ years of cloud infrastructure experience and demonstrated influence with executive and board stakeholders. Success depends on combining deep AI infrastructure expertise with commercial judgment across complex, high-value accounts.

## Salary analysis

Estimated compensation compared with the broader US market for similar roles.

Estimated job medianMarket rate$316,000US market range$240k–$400k0$440k

AI insightThe disclosed annual base salary range is USD 271,000–361,000, with a midpoint of USD 316,000. For a US-based Account CTO or enterprise AI infrastructure technical executive, an estimated market base-salary range is USD 240,000–400,000; total compensation may be higher when equity and performance-based incentives are included.

## Core skills

Skills and capabilities most closely associated with this opportunity.

[AI/ML Infrastructure](https://jobicy.com/jobs?search_keywords=AIML%20Infrastructure.md)[Cloud Architecture](https://jobicy.com/jobs?search_keywords=Cloud%20Architecture.md)[GPU Clusters](https://jobicy.com/jobs?search_keywords=GPU%20Clusters.md)[NVIDIA DGX/HGX](https://jobicy.com/jobs?search_keywords=NVIDIA%20DGXHGX.md)[Enterprise Architecture](https://jobicy.com/jobs?search_keywords=Enterprise%20Architecture.md)[Executive Stakeholder Management](https://jobicy.com/jobs?search_keywords=Executive%20Stakeholder%20Management.md)[Strategic Accounts](https://jobicy.com/jobs?search_keywords=Strategic%20Accounts.md)[Technical Sales](https://jobicy.com/jobs?search_keywords=Technical%20Sales.md)[Distributed Storage](https://jobicy.com/jobs?search_keywords=Distributed%20Storage.md)[Cloud Transformation](https://jobicy.com/jobs?search_keywords=Cloud%20Transformation.md)

Sample interview questionsHow would you create a multi-year AI infrastructure roadmap for a strategic enterprise customer?I would begin by aligning on the customer’s business priorities, AI use cases, growth assumptions, risk constraints, and success metrics. I would assess the current architecture and operating model, then define phased capabilities across compute, networking, storage, data, security, and governance. Each phase would include measurable business value, technical milestones, ownership, and an executive review cadence.

Describe how you would explain the value of a large GPU cluster investment to a CFO and CTO.

I would tailor the discussion to their priorities: financial predictability, time to value, risk, and strategic advantage. I would quantify TCO against alternatives, model utilization and scaling scenarios, connect performance improvements to faster model development or inference capacity, and clearly state operational assumptions. The outcome would be a decision-ready narrative rather than a purely technical specification.

What are the most important architectural considerations for large-scale LLM training?

Key considerations include GPU topology and utilization, high-bandwidth low-latency networking such as InfiniBand or RoCE, distributed storage throughput, checkpointing, data pipeline design, fault tolerance, scheduling, observability, and security. I would also evaluate framework compatibility, model parallelism strategy, inference transition requirements, and the operational expertise required to sustain the environment.

How would you manage a critical technical escalation at an executive customer account?

I would establish a clear incident structure immediately, confirm customer impact and business priority, and assign accountable technical owners. I would provide concise, regular executive updates that distinguish known facts, mitigation actions, risks, and recovery timing. After stabilization, I would lead a blameless review and convert findings into prevention measures, architecture improvements, and agreed customer communications.

How do you balance strategic account requests with broader product strategy?

I evaluate requests through repeatability, market demand, strategic account value, technical feasibility, and opportunity cost. I work with product and engineering teams to distinguish a reusable platform capability from one-off customization, while being transparent with the customer about trade-offs. This approach protects product coherence while ensuring high-value customer insights inform the roadmap.

Lambda, The Superintelligence Cloud, is a leader in AI cloud infrastructure serving tens of thousands of customers. Our customers range from AI researchers to enterprises and hyperscalers. Lambda’s mission is to make compute as ubiquitous as electricity and give everyone the power of superintelligence. One person, one GPU.

If you’d like to build the world’s best AI cloud, join us.

Engineering at Lambda is responsible for building and scaling our cloud offering. Our scope includes the Lambda website, cloud APIs and systems as well as internal tooling for system deployment, management and maintenance.

What You’ll Do

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Strategic Technology Leadership for Key Accounts

Serve as the primary technical liaison for Lambda’s strategic Superintelligence accounts

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Cultivate and sustain executive level technical relationships, establishing Lambda as a trusted technology partner and strategic advisor

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Drive multi-year technology roadmaps aligned with customer business objectives and Lambda’s product portfolio

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Influence customer technology strategy and adoption at the executive level

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Represent Lambda at executive briefings, board meetings, and strategic planning sessions

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Own Technical Strategy and Business Outcomes

Partner with Global Account teams to drive strategic account growth and expansion

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Lead architectural reviews and technology assessments at the enterprise level

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Define and articulate business value propositions, ROI models, and TCO analyses for executive stakeholders

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Orchestrate cross-functional teams including Solutions Engineers, Forward Deployed Engineers, Professional Services, and Product Management

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Own technical escalations and serve as the Executive Technical Sponsor for critical customer initiatives

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Drive adoption of Lambda’s strategic initiatives within key accounts

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Technology Vision and Thought Leadership

Establish yourself as a trusted advisor on AI/ML transformation and cloud strategy

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Guide customers through digital transformation journeys and emerging technology adoption

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Publish thought leadership content, speak at industry events, and represent Lambda in executive forums

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Influence Lambda’s product strategy based on strategic customer needs and market trends

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Mentor and develop technical talent across the organization

You

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Have 15+ years of experience designing, deploying and scaling cloud infrastructure

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Have 6+ years of experience working directly with C-suite executives and senior leadership teams in advisory or consultative capacities

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Have 5+ years driving cloud transformation initiatives at enterprise scale

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Have proven track record of influencing C-suite executives and board-level stakeholders

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Have deep expertise in AI/ML technologies and their business applications

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Have experience with NVIDIA DGX/HGX/MGX systems, InfiniBand &RoCE networking, and large-scale GPU cluster deployments

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Have experience with storage architectures including distributed file systems, object storage, high-performance parallel file systems, and NVMe-based solutions

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Have hands-on experience with LLM training, fine-tuning, and inference at scale

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Have experience with enterprise architecture frameworks and governance models

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Have experience managing or influencing deals worth $1B+ annually

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Have strong business acumen with ability to translate technology into business outcomes

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Have experience navigating complex organizational dynamics and driving consensus

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Have track record of building strategic partnerships and alliances

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Excel at executive communication, presentation, and storytelling

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Demonstrate thought leadership through publications, speaking engagements, or industry recognition

Nice to Have

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MBA or advanced degree in Computer Science, Engineering, or related technical field

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Experience as a CTO, VP of Engineering, Chief Architect, or Technical Fellow at a technology company with $100M+ revenue

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Track record working with AI labs, research institutions, or frontier model companies

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Board advisory experience for technology companies

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Published peer-reviewed research, whitepapers, or patents specifically in distributed computing, GPU acceleration, or large-scale ML training infrastructure

Salary Range Information

The annual salary range for this position has been set based on market data and other factors. However, a salary higher or lower than this range may be appropriate for a candidate whose qualifications differ meaningfully from those listed in the job description.

About Lambda

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Founded in 2012, with 500+ employees, and growing fast

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Our investors notably include TWG Global, US Innovative Technology Fund (USIT), Andra Capital, SGW, Andrej Karpathy, ARK Invest, Fincadia Advisors, G Squared, In-Q-Tel (IQT), KHK & Partners, NVIDIA, Pegatron, Supermicro, Wistron, Wiwynn, Gradient Ventures, Mercato Partners, SVB, 1517, and Crescent Cove

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We have research papers accepted at top machine learning and graphics conferences, including NeurIPS, ICCV, SIGGRAPH, and TOG

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Our values are publicly available: [https://lambda.ai/careers](https://lambda.ai/careers)

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We offer generous cash & equity compensation

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Health, dental, and vision coverage for you and your dependents

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Wellness and commuter stipends for select roles

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401k Plan with 2% company match (USA employees)

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Flexible paid time off plan that we all actually use

Equal Opportunity Employer

Lambda is an Equal Opportunity employer. Applicants are considered without regard to race, color, religion, creed, national origin, age, sex, gender, marital status, sexual orientation and identity, genetic information, veteran status, citizenship, or any other factors prohibited by local, state, or federal law.

Show more

[Apply now >](https://jobicy.com/jobs/152686-account-cto.md)

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