Senior Staff Forward Deployed Engineer, Enterprise AI and Automation

NVIDIA
Santa Clara
Full timeUSD 224,000 - 356,500 annuallyFunction: Data Science & Machine LearningExperience: 12+ yearsEducation: bachelorsSkills: ["Technical leadership","Mentoring","Communication","Product judgment","Collaboration"]

Drive Enterprise AI transformation by embedding with internal NVIDIA teams to discover needs and deliver production AI solutions end-to-end. Own technical delivery across domains such as supply chain, IT operations, SRE, network infrastructure, finance, HR, and security. Build and operate full-stack AI systems using Python, TypeScript, PostgreSQL, Milvus, and Kubernetes, integrating LLMs and multimodal models via standard/OpenAI-compatible APIs. Measure adoption, reliability, and business impact, and help convert deployments into reusable enterprise AI platform capabilities.

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FursaFursa
NVIDIA
NVIDIA
22 hours ago

Senior Staff Forward Deployed Engineer, Enterprise AI and Automation

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

Source: Company careers pageValidated by: Fursa AI
Last checked: 22 hours agoStatus: Live

Job Summary

Drive Enterprise AI transformation by embedding with internal NVIDIA teams to discover needs and deliver production AI solutions end-to-end. Own technical delivery across domains such as supply chain, IT operations, SRE, network infrastructure, finance, HR, and security. Build and operate full-stack AI systems using Python, TypeScript, PostgreSQL, Milvus, and Kubernetes, integrating LLMs and multimodal models via standard/OpenAI-compatible APIs. Measure adoption, reliability, and business impact, and help convert deployments into reusable enterprise AI platform capabilities.
Location: Santa Clara
Employment Type: Full time
Job Function: Data Science & Machine Learning
Seniority: Sr. Manager level

Key Responsibilities

  • •Own technical delivery for enterprise domains (e.g., supply chain, IT operations, SRE, network infrastructure, finance, HR, security) from discovery and architecture through development, deployment, adoption, and continuous improvement.
  • •Design, build, and operate full-stack AI systems using Python, TypeScript, PostgreSQL, vector databases (e.g., Milvus), and Kubernetes.
  • •Prototype and productionize AI capabilities by validating with users and translating feedback into high-quality products.
  • •Ensure production success by measuring adoption, evaluation results, reliability, operational performance, and business impact; establish testing, observability, CI/CD, security, and operational readiness practices.
  • •Identify reusable patterns and collaborate with platform engineering to turn successful deployments into shared Enterprise AI services and frameworks.

Pay and Benefits

Salary: USD 224,000 - 356,500 annually
Equity and Bonus:Equity

Key Requirements

  • •BS/MS (or equivalent) in Computer Science, Software Engineering, or related field, with 12+ years building and operating large-scale production software systems.
  • •Own end-to-end delivery from ambiguous problem definition through architecture, prototyping, productionization, and long-term operation with measurable outcomes.
  • •Strong software engineering across the application stack, with sound architectural tradeoffs for scalability, reliability, performance, security, maintainability, and development velocity.
  • •Hands-on experience building production AI applications using LLMs, agentic architectures, RAG, tool use, workflow orchestration, memory, evaluation systems, guardrails, or intelligent automation.
  • •Demonstrated product/user-experience judgment and the ability to partner with business stakeholders to translate complex requirements into scalable solutions.
Experience:12+ yearsEnterprise AILLMAgentic architecturesRAGProduction software
Education:Bachelor's
Skills:Technical leadershipMentoringCommunicationProduct judgmentCollaboration
Tech Stack:PythonTypeScriptPostgreSQLMilvusVector databasesKubernetesOpenAI-compatible APIsLLMsMultimodal modelsRAGTool useWorkflow orchestrationEvaluation systemsCI/CDObservabilitySecurity

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
Glassdoor: 4.3
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