AI Engineer Jobs at Apple with Visa Sponsorship
AI Engineer jobs at Apple are built around deep research, production-scale systems, and product integration across hardware and software. The company has a consistent track record of sponsoring work visas for AI Engineers, covering multiple nonimmigrant and immigrant pathways for qualified candidates.
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Get Access To All JobsINTRODUCTION
Imagine what you could do here! At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job, and there's no telling what you could accomplish. The people here at Apple don’t just craft products - they build the kind of wonder that’s revolutionized entire industries. It’s the diversity of those people and their ideas that inspires the innovation that runs through everything we do, from amazing technology to industry-leading environmental efforts.
DESCRIPTION
The People Technology team is looking for an AI Enablement Lead to partner with our business owners and engineering teams on re-engineering processes using new emerging technology.
This role sits squarely at the intersection of business strategy, technology, process design, and applied AI. The ideal candidate combines operational judgment with technical fluency - understanding both the realities of People processes and the practical considerations required to deploy AI-enabled workflows responsibly at enterprise scale.
This is a high-ownership, high-visibility role that will help influence how the People organization evolves its operational model over time.
Responsibilities
- Conduct structured assessments across People functions to identify workflows where AI-enabled automation can deliver meaningful improvements in user experience, effectiveness, scalability and accuracy
- Evaluate opportunities based on operational leverage, business value, process complexity, risk profile, governance considerations, and measurable impact
- Identify repetitive manual work, operational bottlenecks, fragmented workflows, and high-volume process areas suitable for intelligent automation
- Build and maintain a prioritized backlog and roadmap of AI deployment opportunities tied to clearly defined operational KPIs and business outcomes
- Map structured and unstructured data flows across enterprise platforms including Workday, ServiceNow, People EDW, collaboration platforms, project management tooling, and knowledge repositories
- Define human-in-the-loop review checkpoints, escalation paths, auditability requirements, and governance controls within deployed workflows
- Configure and operationalize AI-enabled workflows using APIs, MCP servers, orchestration tooling, integration layers, and enterprise operational platforms
- Translate operational requirements into scalable production-ready solutions with appropriate safeguards, monitoring, documentation, and support models
- Ensure deployed solutions remain maintainable, supportable, and operationally sustainable over time
- Operate and monitor deployed agents and AI-enabled workflows against defined operational KPIs including cycle time, exception rates, accuracy, reliability, adoption, and workflow quality
- Manage evaluations, regression testing, and workflow validation following significant model updates, schema changes, process modifications, or operational dependency changes
- Maintain operational documentation including workflow maps, data lineage, escalation models, governance considerations, and change logs
- Partner cross-functionally with People team leadership, operations teams, engineering, governance, security, and platform teams to ensure deployed workflows align with enterprise standards and operational controls
- Surface emerging automation opportunities as operational needs and organizational priorities evolve
- Drive iterative improvement of deployed workflows through operational feedback loops, usage patterns, testing, and ongoing refinement
- Support adoption of AI-enabled workflows through rollout planning, stakeholder engagement, operational enablement, documentation, and training support
- Establish and maintain People-specific knowledge repositories including process documentation, operational narratives, runbooks, LOB context, and workflow guidance
- Ensure knowledge assets remain current, governed, and accessible in ways that improve both workflow reliability and team self-service capabilities
- Contribute to operational best practices for deploying AI-enabled systems responsibly within enterprise People environments
PREFERRED QUALIFICATIONS
- Deep technical understanding of modern AI application architecture, including LLM-powered applications, tool calling, retrieval and grounding, context management, structured outputs, and agentic workflow orchestration.
- Experience designing agentic architectures such as tool-using agents, orchestrator/worker patterns, multi-agent workflows, event-driven agents, approval-based workflows, and human-in-the-loop systems.
- Experience building or integrating solutions using APIs, MCP servers, orchestration frameworks, enterprise integration layers, and reusable agent/tool interfaces.
- Understanding of enterprise hosting and deployment patterns for AI-enabled applications, including runtime environments, environment separation, scalability, reliability, configuration management, and production support.
- Strong knowledge of security patterns for AI and enterprise applications, including authentication, authorization, service identities, secrets management, least-privilege access, secure API design, auditability, and sensitive-data handling.
- Experience with AI evaluation and observability practices, including tracing, logging, regression testing, quality evaluation, latency and reliability monitoring, failure analysis, and production telemetry.
- Understanding of state management, retries, fallbacks, exception handling, escalation paths, and long-running workflow design for production agentic systems.
- Experience working with structured and unstructured enterprise data, including data access patterns, schemas, SQL, retrieval pipelines, knowledge repositories, and enterprise data platforms.
- Familiarity with software engineering practices such as source control, CI/CD, automated testing, release management, environment management, and operational support.
- Experience identifying reusable AI capabilities, integration patterns, shared services, and platform components that can scale across multiple business functions.
- Strong understanding of responsible AI, privacy, governance, and control requirements in environments involving sensitive employee or enterprise data.
- Experience within People, HR technology, People Operations, People Support, or adjacent enterprise business functions is a plus.
MINIMUM QUALIFICATIONS
- 8+ years of experience in enterprise technology, AI enablement, automation, integrations, digital transformation, or related technical roles.
- Strong experience translating complex business and operational requirements into scalable technology solutions.
- Demonstrated experience designing, building, or enabling automated workflows across enterprise systems and business processes.
- Hands-on technical fluency with APIs, integrations, scripting, SQL/data querying, workflow orchestration, and enterprise application platforms.
- Experience working with AI-enabled applications, agentic workflows, or intelligent automation solutions in an enterprise environment.
- Strong understanding of software delivery and production lifecycle concepts, including development, testing, deployment, monitoring, support, and continuous improvement.
- Experience partnering across engineering, business, security, governance, UX, and platform teams to deliver enterprise solutions.
- Ability to evaluate technical feasibility, operational complexity, business value, risk, and scalability when prioritizing automation opportunities.
- Strong communication and stakeholder-management skills with the ability to translate between technical teams and business partners.
- Ability to operate effectively in ambiguous environments, independently shape problems, and drive initiatives from discovery through implementation and adoption.
PAY & BENEFITS
At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $149,200 and $249,000, and your base pay will depend on your skills, qualifications, experience, and location.
Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation.
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.
INTRODUCTION
Imagine what you could do here! At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job, and there's no telling what you could accomplish. The people here at Apple don’t just craft products - they build the kind of wonder that’s revolutionized entire industries. It’s the diversity of those people and their ideas that inspires the innovation that runs through everything we do, from amazing technology to industry-leading environmental efforts.
DESCRIPTION
The People Technology team is looking for an AI Enablement Lead to partner with our business owners and engineering teams on re-engineering processes using new emerging technology.
This role sits squarely at the intersection of business strategy, technology, process design, and applied AI. The ideal candidate combines operational judgment with technical fluency - understanding both the realities of People processes and the practical considerations required to deploy AI-enabled workflows responsibly at enterprise scale.
This is a high-ownership, high-visibility role that will help influence how the People organization evolves its operational model over time.
Responsibilities
- Conduct structured assessments across People functions to identify workflows where AI-enabled automation can deliver meaningful improvements in user experience, effectiveness, scalability and accuracy
- Evaluate opportunities based on operational leverage, business value, process complexity, risk profile, governance considerations, and measurable impact
- Identify repetitive manual work, operational bottlenecks, fragmented workflows, and high-volume process areas suitable for intelligent automation
- Build and maintain a prioritized backlog and roadmap of AI deployment opportunities tied to clearly defined operational KPIs and business outcomes
- Map structured and unstructured data flows across enterprise platforms including Workday, ServiceNow, People EDW, collaboration platforms, project management tooling, and knowledge repositories
- Define human-in-the-loop review checkpoints, escalation paths, auditability requirements, and governance controls within deployed workflows
- Configure and operationalize AI-enabled workflows using APIs, MCP servers, orchestration tooling, integration layers, and enterprise operational platforms
- Translate operational requirements into scalable production-ready solutions with appropriate safeguards, monitoring, documentation, and support models
- Ensure deployed solutions remain maintainable, supportable, and operationally sustainable over time
- Operate and monitor deployed agents and AI-enabled workflows against defined operational KPIs including cycle time, exception rates, accuracy, reliability, adoption, and workflow quality
- Manage evaluations, regression testing, and workflow validation following significant model updates, schema changes, process modifications, or operational dependency changes
- Maintain operational documentation including workflow maps, data lineage, escalation models, governance considerations, and change logs
- Partner cross-functionally with People team leadership, operations teams, engineering, governance, security, and platform teams to ensure deployed workflows align with enterprise standards and operational controls
- Surface emerging automation opportunities as operational needs and organizational priorities evolve
- Drive iterative improvement of deployed workflows through operational feedback loops, usage patterns, testing, and ongoing refinement
- Support adoption of AI-enabled workflows through rollout planning, stakeholder engagement, operational enablement, documentation, and training support
- Establish and maintain People-specific knowledge repositories including process documentation, operational narratives, runbooks, LOB context, and workflow guidance
- Ensure knowledge assets remain current, governed, and accessible in ways that improve both workflow reliability and team self-service capabilities
- Contribute to operational best practices for deploying AI-enabled systems responsibly within enterprise People environments
PREFERRED QUALIFICATIONS
- Deep technical understanding of modern AI application architecture, including LLM-powered applications, tool calling, retrieval and grounding, context management, structured outputs, and agentic workflow orchestration.
- Experience designing agentic architectures such as tool-using agents, orchestrator/worker patterns, multi-agent workflows, event-driven agents, approval-based workflows, and human-in-the-loop systems.
- Experience building or integrating solutions using APIs, MCP servers, orchestration frameworks, enterprise integration layers, and reusable agent/tool interfaces.
- Understanding of enterprise hosting and deployment patterns for AI-enabled applications, including runtime environments, environment separation, scalability, reliability, configuration management, and production support.
- Strong knowledge of security patterns for AI and enterprise applications, including authentication, authorization, service identities, secrets management, least-privilege access, secure API design, auditability, and sensitive-data handling.
- Experience with AI evaluation and observability practices, including tracing, logging, regression testing, quality evaluation, latency and reliability monitoring, failure analysis, and production telemetry.
- Understanding of state management, retries, fallbacks, exception handling, escalation paths, and long-running workflow design for production agentic systems.
- Experience working with structured and unstructured enterprise data, including data access patterns, schemas, SQL, retrieval pipelines, knowledge repositories, and enterprise data platforms.
- Familiarity with software engineering practices such as source control, CI/CD, automated testing, release management, environment management, and operational support.
- Experience identifying reusable AI capabilities, integration patterns, shared services, and platform components that can scale across multiple business functions.
- Strong understanding of responsible AI, privacy, governance, and control requirements in environments involving sensitive employee or enterprise data.
- Experience within People, HR technology, People Operations, People Support, or adjacent enterprise business functions is a plus.
MINIMUM QUALIFICATIONS
- 8+ years of experience in enterprise technology, AI enablement, automation, integrations, digital transformation, or related technical roles.
- Strong experience translating complex business and operational requirements into scalable technology solutions.
- Demonstrated experience designing, building, or enabling automated workflows across enterprise systems and business processes.
- Hands-on technical fluency with APIs, integrations, scripting, SQL/data querying, workflow orchestration, and enterprise application platforms.
- Experience working with AI-enabled applications, agentic workflows, or intelligent automation solutions in an enterprise environment.
- Strong understanding of software delivery and production lifecycle concepts, including development, testing, deployment, monitoring, support, and continuous improvement.
- Experience partnering across engineering, business, security, governance, UX, and platform teams to deliver enterprise solutions.
- Ability to evaluate technical feasibility, operational complexity, business value, risk, and scalability when prioritizing automation opportunities.
- Strong communication and stakeholder-management skills with the ability to translate between technical teams and business partners.
- Ability to operate effectively in ambiguous environments, independently shape problems, and drive initiatives from discovery through implementation and adoption.
PAY & BENEFITS
At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $149,200 and $249,000, and your base pay will depend on your skills, qualifications, experience, and location.
Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation.
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.
See all 249+ AI Engineer Jobs at Apple
Sign up for free to unlock all listings, filter by visa type, and get alerts for new AI Engineer Jobs at Apple.
Get Access To All JobsTips for Finding AI Engineer Jobs at Apple
Align your portfolio to Apple's ML stack
Apple's AI teams prioritize on-device inference, Core ML, and privacy-preserving techniques over cloud-heavy architectures. Showcase projects involving model compression, neural engine optimization, or federated learning to match what their hiring teams are actually evaluating.
Target teams where sponsorship is routine
Apple's Siri, Vision Pro, and silicon teams regularly hire AI Engineers from abroad. Filtering your search to these product lines increases your odds of landing on a team with an established sponsorship workflow rather than one that's navigating it for the first time.
Clarify your visa category before the offer stage
Apple sponsors H-1B, E-3, TN, and H-1B1 visa depending on your nationality. Know which category applies to you before interviews so you can answer recruiter questions about authorization confidently and avoid delays when the offer is drafted.
Prepare degree equivalency documentation early
Apple's AI Engineer roles typically require a bachelor's degree in computer science or a related field. If your credentials are from outside the U.S., get a credential evaluation from a NACES-approved agency before you receive an offer to avoid holding up the LCA filing with DOL.
Use Migrate Mate to find open AI Engineer roles at Apple
AI Engineer openings at Apple that explicitly support visa sponsorship can be hard to identify through general job boards. Use Migrate Mate to filter Apple's listings by visa type and role so you're only applying to positions where sponsorship is confirmed.
Understand Apple's H-1B timeline if you're switching status
If you're on F-1 OPT, your employer must file your H-1B petition with USCIS by April 1 for an October 1 start. Apple's legal team initiates this process months earlier, so engage your recruiter about timing as soon as your offer is verbal, not after signing.
Frequently Asked Questions
Does Apple sponsor H-1B visas for AI Engineers?
Yes, Apple sponsors H-1B visas for AI Engineers. Apple participates in the annual H-1B lottery each April for cap-subject candidates and also files cap-exempt petitions for candidates transitioning from qualifying institutions. The process is handled by Apple's in-house immigration legal team, which coordinates with the recruiting team once an offer is extended.
How do I apply for AI Engineer jobs at Apple?
Applications go through Apple's careers portal at jobs.apple.com, where you can search by team or keyword. Because visa-sponsored roles aren't always labeled clearly on general job boards, browsing through Migrate Mate lets you filter Apple's AI Engineer openings specifically by visa type, saving you from applying to roles where sponsorship isn't available.
Which visa types does Apple commonly use for AI Engineers?
Apple sponsors H-1B for most nationalities, E-3 visa for Australian citizens, TN visa for Canadian and Mexican nationals in qualifying roles, and H-1B1 visa for citizens of Chile and Singapore. For longer-term pathways, Apple also supports EB-2 and EB-3 Green Card sponsorship. F-1 OPT and CPT are available for students earlier in the pipeline.
What qualifications does Apple look for in AI Engineer candidates who need visa sponsorship?
Apple's AI Engineer roles typically require a bachelor's degree at minimum in computer science, electrical engineering, or a closely related field, with a master's or PhD preferred for research-oriented positions. Hands-on experience with frameworks like PyTorch or JAX, familiarity with on-device or edge deployment, and a track record of shipping ML features at scale carry significant weight in the evaluation process.
How do I think about timing when Apple is sponsoring my visa?
If you're relying on the H-1B cap, your employment can't legally begin until October 1 of the fiscal year for which you were selected. Apple's recruiters and immigration counsel typically begin the process months before the April 1 filing deadline, so you'll want your offer finalized and documentation ready no later than February or March to stay on schedule.