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Artificial Intelligence Architect Jobs (NOW HIRING)

M2S Group

Artificial Intelligence Architect

New York, NY · On-site +1

$69.75 - $89.75/hr

About the Role We're hiring an AI Architect to define the technical foundation for all our AI/ML systems including architecture standards, platform decisions, and quality gates that let us deliver ...

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How much do artificial intelligence architect jobs pay per year?

As of Aug 24, 2026, the average yearly pay for artificial intelligence architect in the United States is $128,756.00, according to ZipRecruiter salary data. Most workers in this role earn between $91,000.00 and $166,000.00 per year, depending on experience, location, and employer.

What is an artificial intelligence architect?

An Artificial Intelligence Architect is responsible for designing, developing, and overseeing AI solutions within an organization. They create AI strategies, choose appropriate technologies, and ensure scalable and efficient AI system integration. Their role involves collaborating with data scientists, engineers, and business teams to align AI implementations with company goals. Additionally, they address ethical considerations, model performance, and infrastructure needs to optimize AI deployment.

What are the typical daily responsibilities of an artificial intelligence architect?

Artificial Intelligence Architects typically spend their days designing and implementing AI models, evaluating and selecting appropriate algorithms, and collaborating with data scientists, engineers, and stakeholders to align technical solutions with business objectives. They often oversee data pipelines, guide model optimization, and participate in code reviews to ensure high-quality outputs. Project planning and documentation are also key parts of the role, as is staying current with new developments in AI technologies. This blend of hands-on technical work and cross-team coordination keeps each day dynamic and impactful.

What are the key skills and qualifications needed to thrive as an artificial intelligence architect?

To thrive as an Artificial Intelligence Architect, you need a deep understanding of machine learning, data science, algorithm design, and experience with programming languages like Python and Java, typically supported by a degree in computer science or a related field. Familiarity with AI frameworks (such as TensorFlow, PyTorch), cloud platforms (like AWS, Azure), and certifications in AI or cloud solutions are highly beneficial. Exceptional problem-solving, project management, and cross-functional communication skills help professionals succeed in this collaborative and rapidly-evolving role. These skills are crucial for designing scalable AI systems that meet business goals while adapting to emerging technologies and organizational needs.

What do artificial intelligence architects do?

Artificial Intelligence Architects design and develop AI systems and solutions by analyzing business needs, selecting appropriate algorithms, and integrating AI models into existing infrastructure. They often work with machine learning frameworks, programming languages like Python, and cloud platforms, ensuring scalable and efficient AI deployment. Strong problem-solving skills and knowledge of data science are essential for this role.

What does an artificial intelligence architect do?

An artificial intelligence architect designs and develops AI systems and solutions, including machine learning models, neural networks, and data pipelines. They analyze business needs, select appropriate technologies, and oversee the implementation of AI projects, often requiring knowledge of programming languages like Python and tools such as TensorFlow or PyTorch.
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Artificial Intelligence Architect jobs near you
Infographic showing various Artificial Intelligence Architect job openings in the United States as of August 2026, with employment types broken down into 80% Full Time, and 20% Contract. Highlights an 80% In-person, and 20% Remote job distribution, with an average salary of $128,756 per year, or $61.9 per hour.

Artificial Intelligence Architect

M2S Group

New York, NY • On-site, Remote

$69.75 - $89.75/hr

Full-time

Re-posted yesterday

Job description

About the Role
We're hiring an AI Architect to define the technical foundation for all our AI/ML systems including architecture standards, platform decisions, and quality gates that let us deliver scalable, secure, and governed AI solutions tied directly to business outcomes. You'll sit at the intersection of engineering, data, and business strategy, designing the systems and setting the standards that accelerate AI adoption across the enterprise.
What You'll Do
  • Design the enterprise AI/ML architecture, including reference patterns and multi-entity / multi-tenant architectures with governed data boundaries
  • Evaluate and select AI platforms, frameworks, and cloud services
  • Establish technical standards for model development, testing, and deployment
  • Design agentic search and retrieval systems for enterprise knowledge grounding
  • Review and approve architecture for all AI use cases before they reach production
  • Define data architecture requirements for ML pipelines
  • Lead build vs. buy evaluations for AI tooling
  • Mentor technical team members and drive engineering excellence
  • Stay current on AI/ML technology trends and assess their relevance to our roadmap

Qualifications
  • 8+ years in software or data architecture, with 4+ years focused on ML systems
  • Deep expertise in cloud platforms (AWS, Azure, or GCP) and their ML services
  • Proven experience designing production ML pipelines at enterprise scale
  • Strong understanding of MLOps, model monitoring, and deployment patterns
  • Experience with both traditional ML and modern LLM/GenAI architectures
  • Familiarity with core enterprise infrastructure architecture

Skills
  • Languages: Python, SQL, and Scala for ML and data engineering
  • ML frameworks: PyTorch, TensorFlow, scikit-learn, and Hugging Face
  • MLOps: Docker, Kubernetes, CI/CD, MLflow, and model registries
  • Cloud & data: AWS, Azure, GCP, Spark, Airflow, and feature stores
  • LLM, GenAI & agentic search: RAG, fine-tuning, prompt engineering, vector databases, query planning, tool use, retrieval orchestration, and multi-step reasoning
  • Responsible AI: governance, model monitoring, and security by design
  • Solution mindset: design thinking, trade-off analysis, and pragmatic delivery

*LI-MD1
Equal Opportunity Employer/Protected Veterans/Individuals with Disabilities
This employer is required to notify all applicants of their rights pursuant to federal employment laws. For further information, please review the Know Your Rights notice from the Department of Labor.

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