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Ai System Architect Jobs (NOW HIRING)

GM Financial

Lead System Architect

Irving, TX · Hybrid

From generative AI and cloud-native technologies to peer-led learning and hackathons, our tech ... The Lead Systems Architect - Agentic AI holds a critical role at the intersection of enterprise ...

GM Financial

Lead System Architect

Irving, TX · On-site

From generative AI and cloud-native technologies to peer-led learning and hackathons, our tech ... The Lead Systems Architect - Agentic AI holds a critical role at the intersection of enterprise ...

Cna

System Architect Director - AI Innovation

Chicago, IL

$250K/yr

Systems architecture expertise across distributed systems, cloud-native patterns, APIs/service-based design, event-driven architecture, and scalable workflow solutions. * Applied AI / GenAI depth ...

CNA

System Architect Director - AI Innovation

Chicago, IL · On-site

$250K/yr

Systems architecture expertise across distributed systems, cloud-native patterns, APIs/service-based design, event-driven architecture, and scalable workflow solutions. * Applied AI / GenAI depth ...

Voltai

System Architect

Palo Alto, CA · On-site

$285K/yr

... AI can design and create beyond human cognitive limits. About the Team Backed by Silicon Valley ... About this Role You will define the architecture for advanced compute and hardware systems ...

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Voltai, Inc

System Architect

Palo Alto, CA · On-site

$285K/yr

... AI can design and create beyond human cognitive limits. About the Team Backed by Silicon Valley ... About this Role You will define the architecture for advanced compute and hardware systems ...

Accenture Federal Services

AI Architect

Chantilly, VA · On-site

Lead the end-to-end technical design, development, and implementation of an agentic AI system to orchestrate user queries across heterogeneous data sources. The architect is responsible for defining ...

RecruitTalent LLC.

System Architect

Fredericksburg, VA · On-site

$70 - $80/hr

... AI/ML deployment. * Establish and maintain DevOps/CI-CD pipelines, configuration repositories, and ... System Architecture & Integration: API-based integrations, microservices, SOA, and middleware ...

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Verathon, Inc.

Senior System Architect

Bothell, WA

Perform the full AI/ML lifecycle hands-on, including: * Use-case evaluation and problem definition * Feature engineering and data preparation * Model selection, experimentation, training, and tuning

Verathon, Inc.

Senior System Architect

Bothell, WA · On-site

Perform the full AI/ML lifecycle hands-on, including: * Use-case evaluation and problem definition * Feature engineering and data preparation * Model selection, experimentation, training, and tuning

SK hynix America

AI System Engineer

San Jose, CA

$117K - $160K/yr

AI System Engineer Office Location: San Jose, CA Job Type: Full-Time Work Model: Onsite About SK ... Design and develop next-generation memory solution architecture and hardware prototypes for energy ...

Verathon, Inc.

Senior System Architect

Bothell, WA

Perform the full AI/ML lifecycle hands-on, including: * Use-case evaluation and problem definition * Feature engineering and data preparation * Model selection, experimentation, training, and tuning

Booz Allen Hamilton

System Architect

El Segundo, CA · On-site

$86K - $198K/yr

System Architect The Opportunity: Create, integrate, and apply interdisciplinary digital models of ... Candidate AI Usage Policy AI is a part of our daily work at Booz Allen, and we are committed to the ...

SK hynix America

AI System Engineer

San Jose, CA · On-site

$117K - $160K/yr

AI System Engineer Office Location: San Jose, CA Job Type: Full-Time Work Model: Onsite About SK ... Design and develop next-generation memory solution architecture and hardware prototypes for energy ...

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All JobsAi System Architect Jobs

Ai System Architect information

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$86.5K

$224.3K

$243.5K

How much do ai system architect jobs pay per year?

As of Jul 5, 2026, the average yearly pay for ai system architect in the United States is $224,334.00, according to ZipRecruiter salary data. Most workers in this role earn between $243,000.00 and $243,000.00 per year, depending on experience, location, and employer.

What is the difference between Ai System Architect vs Data Scientist?

AspectAi System ArchitectData Scientist
Required CredentialsBachelor's or master's in CS, AI, or related fields; certifications in AI/MLBachelor's or master's in CS, Statistics, or related fields; certifications in data analysis or ML
Work EnvironmentDesigning AI systems, collaborating with engineers, focusing on architectureAnalyzing data, building models, interpreting results
Employer & Industry UsageTech companies, AI-focused firms, R&D departmentsTech, finance, healthcare, marketing, research organizations

While both roles require knowledge of AI and ML, an Ai System Architect primarily designs and oversees AI system architecture, ensuring integration and scalability. In contrast, a Data Scientist focuses on analyzing data, building models, and deriving insights. The roles often collaborate but differ in their core responsibilities and focus areas.

What are AI System Architects?

AI System Architects are professionals who design, plan, and oversee the development of artificial intelligence systems within organizations. They are responsible for creating the overall architecture for AI solutions, ensuring that different technologies, algorithms, and data sources work together seamlessly. AI System Architects collaborate with data scientists, engineers, and business stakeholders to implement scalable and effective AI-driven products and services. Their role often includes evaluating new technologies, setting best practices, and ensuring the security and scalability of AI systems.

What does an AI systems architect do?

An AI systems architect designs and develops complex artificial intelligence systems, including selecting appropriate algorithms, frameworks, and hardware. They analyze requirements, create system architecture, and ensure integration with existing infrastructure, often using tools like cloud platforms and programming languages such as Python or Java. Strong knowledge of machine learning, data management, and software engineering is essential for this role.

What are the key skills and qualifications needed to thrive as an AI System Architect, and why are they important?

To thrive as an AI System Architect, you need a deep understanding of machine learning, distributed systems, data engineering, and typically a degree in computer science or a related field. Familiarity with cloud platforms (like AWS, GCP, or Azure), AI frameworks (such as TensorFlow or PyTorch), and experience with system design are essential, along with relevant certifications. Strong problem-solving skills, strategic thinking, and effective communication set top candidates apart. These skills ensure the architect can design scalable, efficient, and robust AI solutions that align with business objectives and technical requirements.

What is a $900000 AI job?

A $900,000 AI job typically refers to a high-level position such as an AI Systems Architect or senior AI executive, often involving advanced skills in machine learning, deep learning, and system design. These roles usually require extensive experience, leadership abilities, and may include responsibilities like overseeing AI development projects or strategic planning in technology companies.

What is the salary of an AI architect?

The salary of an AI System Architect typically ranges from $100,000 to $180,000 annually, depending on experience, location, and industry. Senior roles or those with specialized skills in machine learning and deep learning can earn higher compensation, often exceeding $200,000 with bonuses and benefits.

How does an AI System Architect typically collaborate with data scientists and engineers during a project?

An AI System Architect works closely with data scientists to understand the requirements and constraints of AI models and ensures that system infrastructure supports their needs. They collaborate with engineers to design scalable, robust architectures and oversee the integration of AI components into existing systems. Regular communication and joint problem-solving are essential, as architects bridge the gap between high-level AI goals and practical implementation, often facilitating technical discussions and making critical design decisions.

How much do AI systems architects make?

AI systems architects typically earn between $100,000 and $180,000 annually, depending on experience, location, and industry. Senior roles or those with specialized skills in machine learning, cloud platforms, and large-scale system design can command higher salaries. Certifications and a strong technical background often contribute to higher compensation in this field.
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What job categories do people searching Ai System Architect jobs look for? The top searched job categories for Ai System Architect jobs are:
Ai System Architect jobs near you
Infographic showing various Ai System Architect job openings in the United States as of June 2026, with employment types broken down into 3% As Needed, 71% Full Time, 21% Part Time, and 5% Contract. Highlights an 66% Physical, 3% Hybrid, and 31% Remote job distribution, with an average salary of $224,334 per year, or $107.9 per hour.
Lead System Architect

Lead System Architect

GM Financial

Irving, TX • Hybrid

Full-time

Retirement

Posted 4 days ago

GM Financial rating

7.9

Company rating: 7.9 out of 10

Based on 41 frontline employees who took The Breakroom Quiz

63rd of 146 rated vehicle equipment hire

Job description

Why GM Financial Technology
Innovation isn't just a talking point at GM Financial, it's how we operate. From generative AI and cloud-native technologies to peer-led learning and hackathons, our tech teams are building real solutions that make a difference. We're committed to AI-powered transformation, using advanced machine learning and automation to help us reimagine customer interactions and modernize operations, positioning GM Financial as a leader in digital innovation within a dynamic industry.
Join us and discover a workplace where your ideas matter, your development is prioritized, and you can truly make a global impact.

What makes you an ideal candidate?

  • Assess enterprise architecture, infrastructure, and cloud readiness for Agentic AI
  • Evaluate use cases through fit-gap analysis, feasibility, scalability, and risk
  • Define and evolve scalable, modular architectures for Agentic AI and GenAI solutions
  • Design systems across orchestration, tool integration, memory, and reasoning workflows
  • Apply best practices for GenAI (RAG, prompt orchestration, fine-tuning)
  • Establish validation frameworks and performance evaluation (accuracy, reliability, safety)
  • Implement end-to-end observability (tracing, monitoring, metrics, debugging)
  • Lead deployment of enterprise AI solutions in Azure with strong security and governance
  • Integrate AI into cloud-native, microservices environments using modern DevOps practices
  • Partner across teams to translate business needs into technical solutions and drive alignment
  • Promote standards, best practices, and responsible AI adoption
  • Mentor teams and communicate complex AI concepts clearly to diverse stakeholders

Experience

  • 7-10 years of architecture experience required
  • Experience leading technical teams preferred
  • High School Diploma or equivalent required

  • Bachelor's Degree in related field or equivalent work or military experience preferred

What We Offer: Generous benefits package available on day one to include: 401K matching, bonding leave for new parents (12 weeks, 100% paid), tuition assistance, training, GM employee auto discount, community service pay and nine company holidays. 

Our Culture: Our team members define and shape our culture. We have an environment that welcomes new ideas, fosters integrity, and creates a sense of community and belonging. Here we do more than. work - we thrive. 

Compensation: Competitive salary and bonus eligibility; this role is eligible for company vehicle program. 

Work Life Balance: Flexible hybrid work environment, 2-days a week in office. 

About the role: 

The Lead Systems Architect - Agentic AI holds a critical role at the intersection of enterprise architecture, emerging AI capabilities, and business value realization. This role serves both as a technical strategist and a hands-on architecture leader, with a strong emphasis on evaluating how Agentic AI and GenAI capabilities can be effectively and safely integrated into the existing enterprise ecosystem.

As a technical leader, this role is responsible for assessing current architecture and infrastructure, conducting feasibility studies, and mapping business use cases and requirements to the organization's AI and system capabilities. The Lead Systems Architect - Agentic AI ensures that proposed solutions are practical, scalable, observable, and production-ready, while aligning with enterprise standards and constraints.

This role requires deep expertise in Agentic AI and Generative AI architectures, including orchestration patterns, tool usage, memory, reasoning workflows, and decision frameworks. The architect must also ensure robust validation mechanisms, observability frameworks, and production deployment strategies for AI systems.

As a performance leader, this role partners with system architects, engineering teams, and business stakeholders to drive clarity, alignment, and execution, while mentoring teams on modern AI architecture practices, responsible AI principles, and production-grade deployments.

In this role you will: 

  • Define and drive enterprise strategy for Agentic AI and GenAI aligned to business goals
  • Assess systems, cloud, and infrastructure readiness for AI adoption
  • Evaluate AI use cases for feasibility, scalability, cost, risk, and compliance
  • Translate business needs into architecture; identify gaps and recommend solutions
  • Design reference architectures and patterns (orchestration, tools, memory, reasoning)
  • Establish validation and observability approaches (testing, benchmarking, monitoring)
  • Guide production deployment and integration with cloud-native, microservices platforms
  • Advise stakeholders, shape governance and standards, promote Azure adoption, and mentor teams on responsible AI and best practices

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