Architect Visa Sponsorship Jobs in New York
New York is one of the most active markets for architect visa sponsorship jobs in the U.S., driven by a dense concentration of major firms including Skidmore, Owings & Merrill, Gensler, and KPF, all headquartered or with large offices in New York City. Demand spans commercial, residential, and civic projects across NYC, Buffalo, and Albany.
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Get Access To All JobsINTRODUCTION
This role requires on-site presence at our Seneca One Tech Hub in Buffalo, NY, for one week per month.
Founded in 1856, M&T Bank is a regional financial institution with a long-standing commitment to financial strength, community banking, and responsible innovation. The bank invests in technology, data, and processes that improve customer outcomes, strengthen resilience, and support sustainable growth.
Purpose
Provide enterprise architecture leadership for artificial intelligence, Generative AI, agentic systems, and intelligent platforms. Define the architectural foundation, governance, standards, and reusable patterns required to scale AI safely, consistently, and strategically across the enterprise.
This is an enterprise architecture leadership role focused on strategy, standards, governance, and cross-enterprise transformation rather than day-to-day solution delivery. The role aligns AI adoption with business strategy, enterprise capabilities, risk appetite, regulatory obligations, and the long-term operating model.
The role establishes AI as a governed enterprise intelligence layer embedded across platforms, processes, data, and decisioning, rather than as a collection of isolated tools.
Role Impact
- Shape enterprise AI architecture by defining target-state platforms, integration patterns, data and context services, agent architectures, and operating-model implications.
- Establish guardrails through architecture principles, standards, reference patterns, risk tiers, and decision frameworks that enable responsible adoption.
- Enable business transformation by translating strategy into AI-enabled capability and investment roadmaps that augment, automate, or redesign processes.
- De-risk adoption by embedding requirements for security, privacy, model risk, resilience, explainability, auditability, regulatory compliance, and operational control.
- Maintain platform and model optionality by guiding choices across enterprise AI platforms and model providers based on value, cost, performance, interoperability, and risk.
Core Responsibilities
- Define and maintain the enterprise target-state architecture for AI, Generative AI, and agentic systems.
- Establish enterprise principles, standards, reference architectures, and decision frameworks for AI adoption.
- Translate business strategy into AI-enabled capability, platform, and investment roadmaps.
- Define architecture for enterprise AI platforms and services, including Microsoft AI Foundry, Azure OpenAI, Microsoft 365 Copilot, Copilot Studio, Azure AI Search, and approved third-party model providers.
- Establish patterns for model selection and orchestration, evaluation, prompt management, guardrails, telemetry, cost management, resilience, and lifecycle governance.
- Define when to use packaged copilots, platform-based workflows, custom agents, traditional AI/ML, or external models.
- Define enterprise patterns for AI agents, multi-agent workflows, tool use, workload identity, permissions, human-in-the-loop controls, monitoring, auditability, and kill switches.
- Define retrieval-augmented generation and enterprise-context architectures, including standards for AI-ready data, metadata, lineage, sensitivity, access, provenance, vector search, and grounding.
- Lead architecture for Copilot extensibility, Microsoft Graph connectors, plugins, and enterprise integrations, including identity, access control, data loss prevention, information protection, and data residency.
- Embed Responsible AI, model risk, cybersecurity, privacy, content safety, prompt-injection defenses, third-party model risk, and regulatory controls into architecture patterns.
- Define control overlays, risk tiering, evaluation requirements, approval workflows, evidence capture, AI incident response, and ongoing monitoring.
- Lead AI architecture governance through design authorities, architecture reviews, and SDLC checkpoints while maintaining architectural accountability through production and lifecycle management.
- Partner with business, data, technology, cybersecurity, risk, privacy, compliance, engineering, and platform teams to drive implementable decisions and explain investment, risk, and architecture tradeoffs to executive governance bodies.
Key Architecture Deliverables
- Enterprise AI target-state architecture and capability-to-technology roadmaps
- AI platform, agentic, integration, and deployment reference architectures
- RAG, enterprise context, and AI-ready data standards
- Microsoft 365 Copilot and Copilot Studio extensibility patterns
- Model selection, evaluation, deployment, and lifecycle decision frameworks
- AI risk and control overlays, evidence requirements, and review templates
- Agent registry, ownership, permission, monitoring, and lifecycle standards
- AI observability, telemetry, cost, resilience, and incident-response standards
MINIMUM QUALIFICATIONS - REQUIRED
- Bachelor’s degree and 7 years of relevant work experience, or in lieu of a degree, a combined minimum of 11 year's higher education and/or relevant work experience
- 3+ years of hands-on experience with Azure OpenAI Service, Azure AI Studio, Microsoft AI Foundry, or a comparable enterprise AI platform, including production deployments.
- Experience designing cloud-based AI architectures using Azure, AWS, or GCP with modern integration, event, identity, and API-management patterns.
- Experience integrating AI/ML and LLM capabilities into enterprise systems with production-grade monitoring, scaling, resilience, security, and failover.
- Working knowledge of Microsoft 365 Copilot extensibility, Microsoft Graph, connectors, plugins, and Copilot Studio.
- Strong understanding of Responsible AI, evaluation methods, data governance, cybersecurity, privacy, model risk, and AI controls in regulated environments.
- Demonstrated ability to influence senior business, technology, risk, and governance stakeholders and communicate complex tradeoffs clearly.
PREFERRED QUALIFICATIONS
- 5+ years architecting AI/ML or Generative AI solutions in financial services, healthcare, or another highly regulated industry.
- Hands-on experience with Microsoft AI Foundry, multi-agent orchestration, evaluation harnesses, guardrails, and reusable accelerator patterns.
- Production experience with RAG pipelines, vector databases, embedding models, reranking strategies, grounding, and content-safety controls.
- Experience integrating OpenAI, Anthropic Claude, or multi-model architectures with enterprise governance controls.
- Practical experience with model risk governance, including Federal Reserve SR 11-7, OCC 2011-12, and related financial-services regulatory expectations.
- Relevant certifications such as TOGAF, Microsoft Certified: Azure Solutions Architect Expert, or AI/ML specialty credentials.
Managerial / Supervisory Responsibility
Not applicable.
Physical Requirements
Professional desk-based role with periodic business travel.
M&T Bank is committed to fair, competitive, and market-informed pay for our employees. The pay range for this position is $139,700.00 - $232,900.00 Annual (USD). The successful candidate’s particular combination of knowledge, skills, and experience will inform their specific compensation.
LOCATION
Buffalo, New York, United States of America
INTRODUCTION
This role requires on-site presence at our Seneca One Tech Hub in Buffalo, NY, for one week per month.
Founded in 1856, M&T Bank is a regional financial institution with a long-standing commitment to financial strength, community banking, and responsible innovation. The bank invests in technology, data, and processes that improve customer outcomes, strengthen resilience, and support sustainable growth.
Purpose
Provide enterprise architecture leadership for artificial intelligence, Generative AI, agentic systems, and intelligent platforms. Define the architectural foundation, governance, standards, and reusable patterns required to scale AI safely, consistently, and strategically across the enterprise.
This is an enterprise architecture leadership role focused on strategy, standards, governance, and cross-enterprise transformation rather than day-to-day solution delivery. The role aligns AI adoption with business strategy, enterprise capabilities, risk appetite, regulatory obligations, and the long-term operating model.
The role establishes AI as a governed enterprise intelligence layer embedded across platforms, processes, data, and decisioning, rather than as a collection of isolated tools.
Role Impact
- Shape enterprise AI architecture by defining target-state platforms, integration patterns, data and context services, agent architectures, and operating-model implications.
- Establish guardrails through architecture principles, standards, reference patterns, risk tiers, and decision frameworks that enable responsible adoption.
- Enable business transformation by translating strategy into AI-enabled capability and investment roadmaps that augment, automate, or redesign processes.
- De-risk adoption by embedding requirements for security, privacy, model risk, resilience, explainability, auditability, regulatory compliance, and operational control.
- Maintain platform and model optionality by guiding choices across enterprise AI platforms and model providers based on value, cost, performance, interoperability, and risk.
Core Responsibilities
- Define and maintain the enterprise target-state architecture for AI, Generative AI, and agentic systems.
- Establish enterprise principles, standards, reference architectures, and decision frameworks for AI adoption.
- Translate business strategy into AI-enabled capability, platform, and investment roadmaps.
- Define architecture for enterprise AI platforms and services, including Microsoft AI Foundry, Azure OpenAI, Microsoft 365 Copilot, Copilot Studio, Azure AI Search, and approved third-party model providers.
- Establish patterns for model selection and orchestration, evaluation, prompt management, guardrails, telemetry, cost management, resilience, and lifecycle governance.
- Define when to use packaged copilots, platform-based workflows, custom agents, traditional AI/ML, or external models.
- Define enterprise patterns for AI agents, multi-agent workflows, tool use, workload identity, permissions, human-in-the-loop controls, monitoring, auditability, and kill switches.
- Define retrieval-augmented generation and enterprise-context architectures, including standards for AI-ready data, metadata, lineage, sensitivity, access, provenance, vector search, and grounding.
- Lead architecture for Copilot extensibility, Microsoft Graph connectors, plugins, and enterprise integrations, including identity, access control, data loss prevention, information protection, and data residency.
- Embed Responsible AI, model risk, cybersecurity, privacy, content safety, prompt-injection defenses, third-party model risk, and regulatory controls into architecture patterns.
- Define control overlays, risk tiering, evaluation requirements, approval workflows, evidence capture, AI incident response, and ongoing monitoring.
- Lead AI architecture governance through design authorities, architecture reviews, and SDLC checkpoints while maintaining architectural accountability through production and lifecycle management.
- Partner with business, data, technology, cybersecurity, risk, privacy, compliance, engineering, and platform teams to drive implementable decisions and explain investment, risk, and architecture tradeoffs to executive governance bodies.
Key Architecture Deliverables
- Enterprise AI target-state architecture and capability-to-technology roadmaps
- AI platform, agentic, integration, and deployment reference architectures
- RAG, enterprise context, and AI-ready data standards
- Microsoft 365 Copilot and Copilot Studio extensibility patterns
- Model selection, evaluation, deployment, and lifecycle decision frameworks
- AI risk and control overlays, evidence requirements, and review templates
- Agent registry, ownership, permission, monitoring, and lifecycle standards
- AI observability, telemetry, cost, resilience, and incident-response standards
MINIMUM QUALIFICATIONS - REQUIRED
- Bachelor’s degree and 7 years of relevant work experience, or in lieu of a degree, a combined minimum of 11 year's higher education and/or relevant work experience
- 3+ years of hands-on experience with Azure OpenAI Service, Azure AI Studio, Microsoft AI Foundry, or a comparable enterprise AI platform, including production deployments.
- Experience designing cloud-based AI architectures using Azure, AWS, or GCP with modern integration, event, identity, and API-management patterns.
- Experience integrating AI/ML and LLM capabilities into enterprise systems with production-grade monitoring, scaling, resilience, security, and failover.
- Working knowledge of Microsoft 365 Copilot extensibility, Microsoft Graph, connectors, plugins, and Copilot Studio.
- Strong understanding of Responsible AI, evaluation methods, data governance, cybersecurity, privacy, model risk, and AI controls in regulated environments.
- Demonstrated ability to influence senior business, technology, risk, and governance stakeholders and communicate complex tradeoffs clearly.
PREFERRED QUALIFICATIONS
- 5+ years architecting AI/ML or Generative AI solutions in financial services, healthcare, or another highly regulated industry.
- Hands-on experience with Microsoft AI Foundry, multi-agent orchestration, evaluation harnesses, guardrails, and reusable accelerator patterns.
- Production experience with RAG pipelines, vector databases, embedding models, reranking strategies, grounding, and content-safety controls.
- Experience integrating OpenAI, Anthropic Claude, or multi-model architectures with enterprise governance controls.
- Practical experience with model risk governance, including Federal Reserve SR 11-7, OCC 2011-12, and related financial-services regulatory expectations.
- Relevant certifications such as TOGAF, Microsoft Certified: Azure Solutions Architect Expert, or AI/ML specialty credentials.
Managerial / Supervisory Responsibility
Not applicable.
Physical Requirements
Professional desk-based role with periodic business travel.
M&T Bank is committed to fair, competitive, and market-informed pay for our employees. The pay range for this position is $139,700.00 - $232,900.00 Annual (USD). The successful candidate’s particular combination of knowledge, skills, and experience will inform their specific compensation.
LOCATION
Buffalo, New York, United States of America
Architect Job Roles in New York
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Search Architect Jobs in New YorkArchitect Jobs in New York: Frequently Asked Questions
Which companies sponsor visas for architects in New York?
New York's largest architecture firms are among the most active visa sponsors in the country. Firms like Skidmore, Owings & Merrill, Kohn Pedersen Fox, Gensler, HOK, and Perkins&Will have consistent histories of filing H-1B visa petitions for architect roles. Large engineering and construction firms with in-house design teams, such as AECOM and WSP, also sponsor architects regularly across their New York offices.
Which visa types are most common for architect roles in New York?
The H-1B is the most common visa category for architects in New York, as architecture qualifies as a specialty occupation requiring at least a bachelor's degree in architecture. Architects from Canada and Mexico may also qualify under the TN visa. Those with exceptional credentials, such as nationally recognized design awards or significant published work, sometimes pursue the O-1A. All pathways require employer sponsorship.
Which cities in New York have the most architect sponsorship jobs?
New York City accounts for the overwhelming majority of architect visa sponsorship jobs in the state, particularly in Manhattan where global and national firms are concentrated. Buffalo has a smaller but growing design sector tied to ongoing urban revitalization projects. Albany sees some demand through government and institutional projects. For most internationally trained architects, NYC is the primary target market in New York State.
How to find architect visa sponsorship jobs in New York?
Migrate Mate lets you filter architect jobs specifically by visa sponsorship availability and state, making it straightforward to identify New York firms actively hiring international candidates. Because many architecture firms do not advertise sponsorship willingness in standard job postings, using a platform like Migrate Mate that surfaces this data directly saves significant time. Focus your search on established firms with 50 or more employees, as they are more likely to have dedicated HR processes for sponsorship.
Are there state-specific factors architects should know when pursuing sponsorship in New York?
New York State requires architects to hold a license from the New York State Education Department to practice independently, though many sponsored roles at firms hire candidates who are working toward licensure under the Architectural Experience Program. The Department of Labor's prevailing wage determination for H-1B petitions is based on the New York City metropolitan area wage level, which is among the highest in the country, so employer cost considerations are a real factor in sponsorship decisions.
What is the prevailing wage for sponsored architect jobs in New York?
U.S. employers sponsoring a visa must pay at least the prevailing wage, which is what workers in the same role, area, and experience level typically earn. The Department of Labor sets this rate to make sure companies aren't hiring foreign workers simply because they'd accept lower pay than a U.S. worker. It varies by job title, location, and experience. You can look up current prevailing wage rates for any occupation and location using the OFLC Wage Search page.