AI Engineer Jobs in Santa Clara, CA
AI Engineer jobs in Santa Clara are concentrated in Silicon Valley's core tech corridor, with demand running high across semiconductor firms, cloud infrastructure companies, and enterprise software providers clustered in the city's industrial parks near Great America Parkway and the Central Expressway belt. Employers actively hiring include NVIDIA, AMD, and ServiceNow. Scan the live roles below and apply to whichever ones fit.
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Showing 5 of 1,084+ AI Engineer jobs
It all started when engineer Fred Luddy wrote code that automated a tedious task for his coworker, Phyllis. She cried tears of joy. That moment inspired Fred to build a company that could do that for everyone—freeing people from busywork so they could focus on meaningful work. Today, ServiceNow is the AI control tower for business reinvention. Our ServiceNow AI platform brings together any AI, any data, and any workflow— helping 85% of the Fortune 500® work smarter, faster, and better. We're building an AI-native culture where technology and talent are unstoppable together. And we're just getting started.
Join us to put AI to work for people.
Job Description
We are seeking a Senior Staff Engineer (IC5) who will set the technical vision and architecture across AI-native and cloud-native systems. The IC5 engineer is a strategic technical leader who drives innovation, shapes engineering culture, and influences the direction of the platform. They work on the highest-impact, most complex problems—defining approaches for novel AI/ML challenges, establishing best practices at scale, and ensuring the organization's technical strategy aligns with business objectives. This role combines deep technical expertise with broad systems thinking, organizational influence, and the ability to mentor and develop senior engineers. IC5 engineers are trusted advisors to leadership and across the organization.
What you get to do in this role:
- Define technical vision and strategy for AI-native and cloud-native systems; establish multi-year technology roadmaps and architectural patterns
- Lead the development of core platforms and infrastructure that enable AI-native development at scale (evaluation frameworks, monitoring, security, deployment)
- Drive adoption of emerging AI/ML technologies, frameworks, and best practices; assess new services and tools for organizational fit
- Establish and evolve technical standards, architectural principles, and engineering excellence standards across the organization
- Own the technical roadmap for critical business initiatives involving AI; evaluate feasibility and set realistic timelines
- Champion investment in foundational improvements (refactoring, testing infrastructure, monitoring, security) that have organization-wide impact
- Influence platform-level decisions involving cost, latency, reliability, and model quality; balance business objectives with technical constraints
- Stay at the forefront of AI/ML research and industry trends; translate research into practical applications for the business
- Mentor and develop senior engineers (IC3/IC4) and engineering leaders; support their growth into leadership and architectural roles
- Lead technical hiring; assess candidates at senior levels and contribute to building a world-class engineering team
- Establish and enforce engineering culture focused on technical excellence, learning, ownership, and collaboration
- Lead by example in code quality, testing discipline, security practices, and responsible AI principles
- Support manager and team leadership development; provide technical guidance to engineering managers and team leads
- Conduct architectural and design reviews; provide critical feedback that shapes the quality of technical decisions across the organization
- Foster knowledge sharing through documentation, technical talks, open-source contributions, and community engagement
- Create and refine career paths and professional development opportunities for engineering team members
- Design and architect large, complex systems involving multiple teams, cloud infrastructure, and sophisticated AI/ML components
- Lead the design of evaluation frameworks, observability systems, and production monitoring for AI-driven features at scale
- Establish security architecture and responsible AI guardrails that scale across the platform
- Design high-performance data platforms, embedding systems, and retrieval pipelines that serve organization-wide needs
- Evaluate and guide adoption of new cloud services, managed AI services, and technologies
- Drive architectural decisions that balance competing concerns: performance, cost, scalability, reliability, developer experience, and business value
- Conduct research and prototyping on novel technical approaches; lead exploration of emerging AI/ML techniques
- Lead root cause analysis and architectural reviews for critical incidents; drive improvements to prevent recurrence
- Communicate technical vision and strategy to executives, product leadership, and engineering teams; influence organizational priorities
- Partner with product, design, and domain specialists to define ambitious technical roadmaps aligned with business strategy
- Represent the engineering organization in high-stakes customer and partnership discussions; build credibility and trust
- Lead or contribute to technical due diligence for acquisitions, partnerships, and strategic technology evaluations
- Translate complex AI/ML concepts, trade-offs, and limitations for audiences ranging from technical engineers to executive leadership
- Advocate for technical health, engineering culture, and long-term sustainability over short-term pressures
- Participate in industry forums, conferences, and communities; enhance the organization's external reputation
- Lead technical interviews and design discussions; mentor interviewing skills across the engineering organization
- Develop innovative solutions to the organization's most complex technical challenges, particularly around AI/ML integration and distributed systems
- Prototype and validate new approaches; share learnings and best practices across the organization
- Contribute to critical code paths and architectures; model best practices in code quality, testing, and maintainability
- Build evaluation frameworks, monitoring systems, and testing infrastructure that scale across the organization
- Implement security best practices, responsible AI guardrails, and compliance mechanisms that serve as templates for the organization
- Work with cloud services, managed AI services, Kubernetes, and infrastructure-as-code at an architectural level
- Troubleshoot and resolve the most complex production issues; establish practices to prevent future incidents
- Contribute to open-source projects, research initiatives, or industry collaboration where aligned with business strategy
- Define platform architecture and integration patterns for AI-native ServiceNow applications
- Establish best practices and architectural standards for ServiceNow development across the organization
- Lead technical decisions on ServiceNow platform capabilities vs. custom development trade-offs
- Drive adoption of ServiceNow platform features and managed services; evaluate and recommend platform upgrades
- Partner with ServiceNow product teams and technical account managers on advanced integrations and customizations
- Mentor senior engineers on ServiceNow platform architecture and advanced development patterns
- Ensure applications remain compatible with ServiceNow platform updates and evolution
- Shape organizational approach to customer support and issue resolution; establish standards for response and resolution
- Lead customer-critical incident response and complex troubleshooting; provide technical escalation path
- Engage with strategic customers on technical topics, roadmap alignment, and complex integration challenges
- Gather and synthesize customer feedback to inform product and platform strategy
- Establish programs and practices that improve customer experience and reduce support burden
- Work with customer success leadership to align technical capabilities with customer success metrics
- Lead technical due diligence and support in customer selection and onboarding processes
Qualifications
To Be Successful in this role you have:
- 12+ years of software development experience with a Bachelor's degree; OR 8+ years with a Master's degree; OR 5+ years with a PhD; OR equivalent work experience
- 4+ years in cloud-native and AI-native systems or equivalent senior-level roles
- 5+ years of experience with LLM/AI systems at scale, including prompt engineering, agent design, retrieval systems, and production AI/ML services
- 5+ years of hands-on experience building and scaling systems with third-party AI/ML services and platform APIs across multiple cloud providers
- 3+ years of experience designing and building applications on platform-as-a-service or SaaS platforms; deep expertise with ServiceNow platform at scale
- Expert-level proficiency in Python, Java, and JavaScript/GlideScript; deep expertise in ServiceNow scripting, APIs, and platform architecture
- Demonstrated expertise in distributed systems design, microservices architecture, and large-scale systems
- Proven track record designing high-performance, mission-critical data pipelines, embedding systems, and vector databases
- Expert knowledge of LLM orchestration frameworks, RAG architectures, retrieval optimization, and vector database technologies
- Deep expertise with cloud computing (AWS/GCP/Azure), managed AI services, and infrastructure-as-code
- Strong background in Kubernetes, containerization, and cloud-native deployment patterns
- Expertise in building evaluation frameworks, metrics systems, and production monitoring for AI/ML systems
- Experience with and strong opinions about secure coding practices, responsible AI, and compliance requirements
- Exceptional communication skills; ability to influence across levels of technical seniority and non-technical audiences; demonstrated customer engagement experience
- Proven ability to lead large, cross-functional technical initiatives; track record of significant technical accomplishments
- Strong background in software architecture, system design, and technical strategy; experience shaping platform strategy and roadmap
- Experience mentoring senior engineers, engineering managers, or technical leaders
- Experience leading customer-critical initiatives or providing technical leadership on strategic accounts
- Bachelor's degree in computer science, engineering, or related field; advanced degree or significant AI/ML research/publications is a plus
- Active engagement with the broader engineering and AI/ML community (conferences, publications, open-source, etc.)
- Demonstrated thought leadership in AI-native development, cloud architecture, or software engineering
Additional Information
Work Personas
We approach our distributed world of work with flexibility and trust. Work personas (flexible, remote, or required in office) are categories that are assigned to ServiceNow employees depending on the nature of their work and their assigned work location. Learn more here. To determine eligibility for a work persona, ServiceNow may confirm the distance between your primary residence and the closest ServiceNow office using a third-party service.
Equal Opportunity Employer
ServiceNow is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, national origin, age, disability, gender identity, veteran status, or any other category protected by law. In addition, all qualified applicants with arrest or conviction records will be considered for employment in accordance with legal requirements.
Accommodations
We strive to create an accessible and inclusive experience for all candidates. If you require a reasonable accommodation to complete any part of the application process, or are unable to use this online application and need an alternative method to apply, please contact globaltalentss@servicenow.com for assistance.
Export Control Regulations
For positions requiring access to controlled technology subject to export control regulations, including the U.S. Export Administration Regulations (EAR), ServiceNow may be required to obtain export control approval from government authorities for certain individuals. All employment is contingent upon ServiceNow obtaining any export license or other approval that may be required by relevant export control authorities.
From Fortune. ©2026 Fortune Media IP Limited. All rights reserved. Used under license.
It all started when engineer Fred Luddy wrote code that automated a tedious task for his coworker, Phyllis. She cried tears of joy. That moment inspired Fred to build a company that could do that for everyone—freeing people from busywork so they could focus on meaningful work. Today, ServiceNow is the AI control tower for business reinvention. Our ServiceNow AI platform brings together any AI, any data, and any workflow— helping 85% of the Fortune 500® work smarter, faster, and better. We're building an AI-native culture where technology and talent are unstoppable together. And we're just getting started.
Join us to put AI to work for people.
Job Description
We are seeking a Senior Staff Engineer (IC5) who will set the technical vision and architecture across AI-native and cloud-native systems. The IC5 engineer is a strategic technical leader who drives innovation, shapes engineering culture, and influences the direction of the platform. They work on the highest-impact, most complex problems—defining approaches for novel AI/ML challenges, establishing best practices at scale, and ensuring the organization's technical strategy aligns with business objectives. This role combines deep technical expertise with broad systems thinking, organizational influence, and the ability to mentor and develop senior engineers. IC5 engineers are trusted advisors to leadership and across the organization.
What you get to do in this role:
- Define technical vision and strategy for AI-native and cloud-native systems; establish multi-year technology roadmaps and architectural patterns
- Lead the development of core platforms and infrastructure that enable AI-native development at scale (evaluation frameworks, monitoring, security, deployment)
- Drive adoption of emerging AI/ML technologies, frameworks, and best practices; assess new services and tools for organizational fit
- Establish and evolve technical standards, architectural principles, and engineering excellence standards across the organization
- Own the technical roadmap for critical business initiatives involving AI; evaluate feasibility and set realistic timelines
- Champion investment in foundational improvements (refactoring, testing infrastructure, monitoring, security) that have organization-wide impact
- Influence platform-level decisions involving cost, latency, reliability, and model quality; balance business objectives with technical constraints
- Stay at the forefront of AI/ML research and industry trends; translate research into practical applications for the business
- Mentor and develop senior engineers (IC3/IC4) and engineering leaders; support their growth into leadership and architectural roles
- Lead technical hiring; assess candidates at senior levels and contribute to building a world-class engineering team
- Establish and enforce engineering culture focused on technical excellence, learning, ownership, and collaboration
- Lead by example in code quality, testing discipline, security practices, and responsible AI principles
- Support manager and team leadership development; provide technical guidance to engineering managers and team leads
- Conduct architectural and design reviews; provide critical feedback that shapes the quality of technical decisions across the organization
- Foster knowledge sharing through documentation, technical talks, open-source contributions, and community engagement
- Create and refine career paths and professional development opportunities for engineering team members
- Design and architect large, complex systems involving multiple teams, cloud infrastructure, and sophisticated AI/ML components
- Lead the design of evaluation frameworks, observability systems, and production monitoring for AI-driven features at scale
- Establish security architecture and responsible AI guardrails that scale across the platform
- Design high-performance data platforms, embedding systems, and retrieval pipelines that serve organization-wide needs
- Evaluate and guide adoption of new cloud services, managed AI services, and technologies
- Drive architectural decisions that balance competing concerns: performance, cost, scalability, reliability, developer experience, and business value
- Conduct research and prototyping on novel technical approaches; lead exploration of emerging AI/ML techniques
- Lead root cause analysis and architectural reviews for critical incidents; drive improvements to prevent recurrence
- Communicate technical vision and strategy to executives, product leadership, and engineering teams; influence organizational priorities
- Partner with product, design, and domain specialists to define ambitious technical roadmaps aligned with business strategy
- Represent the engineering organization in high-stakes customer and partnership discussions; build credibility and trust
- Lead or contribute to technical due diligence for acquisitions, partnerships, and strategic technology evaluations
- Translate complex AI/ML concepts, trade-offs, and limitations for audiences ranging from technical engineers to executive leadership
- Advocate for technical health, engineering culture, and long-term sustainability over short-term pressures
- Participate in industry forums, conferences, and communities; enhance the organization's external reputation
- Lead technical interviews and design discussions; mentor interviewing skills across the engineering organization
- Develop innovative solutions to the organization's most complex technical challenges, particularly around AI/ML integration and distributed systems
- Prototype and validate new approaches; share learnings and best practices across the organization
- Contribute to critical code paths and architectures; model best practices in code quality, testing, and maintainability
- Build evaluation frameworks, monitoring systems, and testing infrastructure that scale across the organization
- Implement security best practices, responsible AI guardrails, and compliance mechanisms that serve as templates for the organization
- Work with cloud services, managed AI services, Kubernetes, and infrastructure-as-code at an architectural level
- Troubleshoot and resolve the most complex production issues; establish practices to prevent future incidents
- Contribute to open-source projects, research initiatives, or industry collaboration where aligned with business strategy
- Define platform architecture and integration patterns for AI-native ServiceNow applications
- Establish best practices and architectural standards for ServiceNow development across the organization
- Lead technical decisions on ServiceNow platform capabilities vs. custom development trade-offs
- Drive adoption of ServiceNow platform features and managed services; evaluate and recommend platform upgrades
- Partner with ServiceNow product teams and technical account managers on advanced integrations and customizations
- Mentor senior engineers on ServiceNow platform architecture and advanced development patterns
- Ensure applications remain compatible with ServiceNow platform updates and evolution
- Shape organizational approach to customer support and issue resolution; establish standards for response and resolution
- Lead customer-critical incident response and complex troubleshooting; provide technical escalation path
- Engage with strategic customers on technical topics, roadmap alignment, and complex integration challenges
- Gather and synthesize customer feedback to inform product and platform strategy
- Establish programs and practices that improve customer experience and reduce support burden
- Work with customer success leadership to align technical capabilities with customer success metrics
- Lead technical due diligence and support in customer selection and onboarding processes
Qualifications
To Be Successful in this role you have:
- 12+ years of software development experience with a Bachelor's degree; OR 8+ years with a Master's degree; OR 5+ years with a PhD; OR equivalent work experience
- 4+ years in cloud-native and AI-native systems or equivalent senior-level roles
- 5+ years of experience with LLM/AI systems at scale, including prompt engineering, agent design, retrieval systems, and production AI/ML services
- 5+ years of hands-on experience building and scaling systems with third-party AI/ML services and platform APIs across multiple cloud providers
- 3+ years of experience designing and building applications on platform-as-a-service or SaaS platforms; deep expertise with ServiceNow platform at scale
- Expert-level proficiency in Python, Java, and JavaScript/GlideScript; deep expertise in ServiceNow scripting, APIs, and platform architecture
- Demonstrated expertise in distributed systems design, microservices architecture, and large-scale systems
- Proven track record designing high-performance, mission-critical data pipelines, embedding systems, and vector databases
- Expert knowledge of LLM orchestration frameworks, RAG architectures, retrieval optimization, and vector database technologies
- Deep expertise with cloud computing (AWS/GCP/Azure), managed AI services, and infrastructure-as-code
- Strong background in Kubernetes, containerization, and cloud-native deployment patterns
- Expertise in building evaluation frameworks, metrics systems, and production monitoring for AI/ML systems
- Experience with and strong opinions about secure coding practices, responsible AI, and compliance requirements
- Exceptional communication skills; ability to influence across levels of technical seniority and non-technical audiences; demonstrated customer engagement experience
- Proven ability to lead large, cross-functional technical initiatives; track record of significant technical accomplishments
- Strong background in software architecture, system design, and technical strategy; experience shaping platform strategy and roadmap
- Experience mentoring senior engineers, engineering managers, or technical leaders
- Experience leading customer-critical initiatives or providing technical leadership on strategic accounts
- Bachelor's degree in computer science, engineering, or related field; advanced degree or significant AI/ML research/publications is a plus
- Active engagement with the broader engineering and AI/ML community (conferences, publications, open-source, etc.)
- Demonstrated thought leadership in AI-native development, cloud architecture, or software engineering
Additional Information
Work Personas
We approach our distributed world of work with flexibility and trust. Work personas (flexible, remote, or required in office) are categories that are assigned to ServiceNow employees depending on the nature of their work and their assigned work location. Learn more here. To determine eligibility for a work persona, ServiceNow may confirm the distance between your primary residence and the closest ServiceNow office using a third-party service.
Equal Opportunity Employer
ServiceNow is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, national origin, age, disability, gender identity, veteran status, or any other category protected by law. In addition, all qualified applicants with arrest or conviction records will be considered for employment in accordance with legal requirements.
Accommodations
We strive to create an accessible and inclusive experience for all candidates. If you require a reasonable accommodation to complete any part of the application process, or are unable to use this online application and need an alternative method to apply, please contact globaltalentss@servicenow.com for assistance.
Export Control Regulations
For positions requiring access to controlled technology subject to export control regulations, including the U.S. Export Administration Regulations (EAR), ServiceNow may be required to obtain export control approval from government authorities for certain individuals. All employment is contingent upon ServiceNow obtaining any export license or other approval that may be required by relevant export control authorities.
From Fortune. ©2026 Fortune Media IP Limited. All rights reserved. Used under license.
See All 1,084+ AI Engineer Jobs in Santa Clara
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Find AI Engineer JobsAI Engineer Job Market in Santa Clara
Who's Hiring
- NVIDIA315
- AMD157
- ServiceNow87
- Palo Alto Networks87
- Foxconn52
Top Industries Hiring
- Technology & Software157
- Electronics & Hardware52
- Science & Research35
- Medical Devices17
- Law & Legal Services17
AI Engineer Jobs in Santa Clara: Frequently Asked Questions
How do I get a ai engineer job in Santa Clara?
Target Santa Clara's dominant employer types: semiconductor companies, cloud platform teams, and enterprise software firms concentrated along the Great America Parkway corridor and near Mission College Boulevard. Candidates with hands-on experience in LLM fine-tuning, MLOps pipelines, or GPU-accelerated inference stand out locally. Networking through Silicon Valley AI meetups and contributing to open-source projects that local engineering teams actively watch also gives applicants a meaningful edge in this market.
Which companies hire ai engineers in Santa Clara?
Companies currently hiring ai engineers in Santa Clara include NVIDIA, AMD, and ServiceNow, per current listings on Migrate Mate as of September 2026. Santa Clara's employer mix skews heavily toward established tech giants and fast-growing semiconductor firms, with a smaller but active cohort of AI-native startups based in the city's newer office parks.
Are there remote ai engineer jobs in Santa Clara?
Yes, though many roles require on-site access to specialized hardware like GPU clusters or lab environments. About 58% of ai engineer openings tied to Santa Clara are remote or hybrid as of September 2026, with remote arrangements most common for roles focused on model development, data pipeline engineering, and research rather than hardware integration or deployment infrastructure.
How can I get a ai engineer job in Santa Clara with little or no experience?
The most realistic entry path in Santa Clara is targeting associate ML engineer or AI research assistant roles at mid-size enterprise software companies and semiconductor firms, which tend to hire junior candidates who can demonstrate project work even without professional experience. Building a portfolio using publicly available datasets, contributing to open-source AI frameworks, and pursuing internships at Santa Clara's larger tech campuses are the moves that most consistently open doors locally.
Which industries hire the most ai engineers in Santa Clara?
The sectors hiring the most ai engineers in Santa Clara are Technology & Software, Electronics & Hardware, and Science & Research, based on current listings on Migrate Mate as of September 2026. Santa Clara's position as a global headquarters hub for semiconductor design and cloud infrastructure makes these sectors especially active, with engineering teams frequently building proprietary AI tooling tied directly to hardware product lines.
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