NVIDIA

2 weeks ago

Senior Technical Marketing Engineer, Enterprise AI Software

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 29 minutes agoStatus: Live

Job Summary

Build technical content and developer journeys that accelerate adoption of NVIDIA’s enterprise AI software. Bridge the enterprise AI platform stack with developers, partners, solution architects, and customers by creating demos, reference examples, deployment guides, docs-as-code workflows, and publishable assets. Help teams understand how NVIDIA AI Enterprise, NIM microservices, Dynamo, NeMo, RAG/agentic AI patterns, inference platforms, and Kubernetes-based deployments fit together end to end.

Location: Santa Clara, United States

Workplace: Hybrid

Employment Type: Full time

Job Function: Marketing & Growth

Seniority: Mid level

Key Responsibilities

•Refine developer, user, and agent journeys with documentation, code examples, demos, and deployment guidance.
•Showcase enterprise AI software workflows by building demos, reference examples, notebooks, and sample applications across model development, inference, RAG/agentic AI, evaluation, deployment, and operations.
•Create public-facing technical assets including product documentation, deployment guides, reference architectures, tutorials, blogs, whitepapers, presentations, webinars, demo videos, and code examples.
•Develop automation and docs-as-code workflows using Git-based documentation, CI/CD, scripts, templates, and AI-assisted docs where appropriate.
•Enable the field and partner ecosystem by supporting solution architects, sales teams, cloud partners, ISVs, and ecosystem teams with technical assets and feedback-driven improvements.

Pay and Benefits

Salary: USD 200,000 - 322,000 annually

Equity and Bonus:Equity

Key Requirements

•BS or MS in Computer Science, Engineering, AI/ML, Data Science (or equivalent technical experience).
•12+ years of proven experience in technical marketing engineering, software development, developer relations, solution architecture, technical writing, product engineering, or a related technical role.
•Hands-on experience building, deploying, or explaining AI/ML, generative AI, RAG, agentic AI, LLM-based applications, inference services, or enterprise software workflows.
•Experience creating customer-facing technical assets such as product documentation, deployment guides, code examples, tutorials, whitepapers, blog posts, presentations, webinars, or demo videos.
•Proven experience with cloud-native development and deployment patterns including containers, Kubernetes, Helm, APIs, SDKs, CI/CD, and Git-based workflows.

Experience:12+ yearsGenerative AIRAGAgentic AILLM-based applicationsDeveloper relationsCloud-nativeOpen source

Education:Bachelor's

Skills:Technical judgmentCommunicationCross-functional collaborationPrioritizationTranslating complex details into content

Tech Stack:NVIDIA AI EnterpriseNIM microservicesDynamoNeMoRAGAgentic AIKubernetesHelmAPIsSDKsCI/CDGitTensorRTTriton Inference ServerRAPIDSCUDADGX CloudRun:aiGPU OperatorNetwork Operator

Company Brief

NVIDIA

Designs and manufactures GPUs, AI accelerators, and system-on-chip products for gaming, data centers, professional visualization, and automotive markets, enabling advanced graphics, AI, and high-performance computing solutions worldwide.

Industry: Electronics Manufacturing

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: Santa Clara, United States

Founded: 1993

Glassdoor: 4.3

Website LinkedIn Glassdoor

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NVIDIA

2 weeks ago

Senior Technical Marketing Engineer, Enterprise AI Software

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 29 minutes agoStatus: Live

Job Summary

Location: Santa Clara, United States

Workplace: Hybrid

Employment Type: Full time

Job Function: Marketing & Growth

Seniority: Mid level

Key Responsibilities

•Refine developer, user, and agent journeys with documentation, code examples, demos, and deployment guidance.
•Showcase enterprise AI software workflows by building demos, reference examples, notebooks, and sample applications across model development, inference, RAG/agentic AI, evaluation, deployment, and operations.
•Create public-facing technical assets including product documentation, deployment guides, reference architectures, tutorials, blogs, whitepapers, presentations, webinars, demo videos, and code examples.
•Develop automation and docs-as-code workflows using Git-based documentation, CI/CD, scripts, templates, and AI-assisted docs where appropriate.
•Enable the field and partner ecosystem by supporting solution architects, sales teams, cloud partners, ISVs, and ecosystem teams with technical assets and feedback-driven improvements.

Pay and Benefits

Salary: USD 200,000 - 322,000 annually

Equity and Bonus:Equity

Key Requirements

•BS or MS in Computer Science, Engineering, AI/ML, Data Science (or equivalent technical experience).
•12+ years of proven experience in technical marketing engineering, software development, developer relations, solution architecture, technical writing, product engineering, or a related technical role.
•Hands-on experience building, deploying, or explaining AI/ML, generative AI, RAG, agentic AI, LLM-based applications, inference services, or enterprise software workflows.
•Experience creating customer-facing technical assets such as product documentation, deployment guides, code examples, tutorials, whitepapers, blog posts, presentations, webinars, or demo videos.
•Proven experience with cloud-native development and deployment patterns including containers, Kubernetes, Helm, APIs, SDKs, CI/CD, and Git-based workflows.

Experience:12+ yearsGenerative AIRAGAgentic AILLM-based applicationsDeveloper relationsCloud-nativeOpen source

Education:Bachelor's

Skills:Technical judgmentCommunicationCross-functional collaborationPrioritizationTranslating complex details into content

Tech Stack:NVIDIA AI EnterpriseNIM microservicesDynamoNeMoRAGAgentic AIKubernetesHelmAPIsSDKsCI/CDGitTensorRTTriton Inference ServerRAPIDSCUDADGX CloudRun:aiGPU OperatorNetwork Operator

Company Brief

NVIDIA

Industry: Electronics Manufacturing

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: Santa Clara, United States

Founded: 1993

Glassdoor: 4.3

Website LinkedIn Glassdoor