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Ai Platform Engineer Jobs in Raleigh, NC (NOW HIRING)

Motion Recruitment

Lead Machine Learning Engineer

Raleigh, NC · On-site

$91K - $120K/yr

Their Global AI Platform Team builds the foundational infrastructure behind next-generation AI ... We are seeking a Sr. Machine Learning Engineer to define and lead the architecture of scalable AI ...

Jaggaer

Architect, AI & Agentic Platforms

Durham, NC · On-site +1

... engineering, and data science teams to build the technology strategy and direction along with contributing to enhance our core product suite stack and an AI platform that integrates LLMs, multi-agent ...

Jaggaer

Architect, AI & Agentic Platforms

Durham, NC · On-site

... engineering, and data science teams to build the technology strategy and direction along with contributing to enhance our core product suite stack and an AI platform that integrates LLMs, multi-agent ...

GEI Consultants

AI Engineer

Cary, NC · On-site

$110K - $150K/yr

The AI Engineer is responsible for the development of AI solutions, typically leveraging pretrained ... This role works closely with solution architects and platform teams to ensure AI solutions are ...

GEI Consultants

AI Engineer

Cary, NC · On-site

The AI Engineer is responsible for the development of AI solutions, typically leveraging pretrained ... This role works closely with solution architects and platform teams to ensure AI solutions are ...

Jaggaer

Architect, AI & Agentic Platforms

Durham, NC · On-site +1

... engineering, and data science teams to build the technology strategy and direction along with contributing to enhance our core product suite stack and an AI platform that integrates LLMs, multi-agent ...

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Ai Platform Engineer information

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How much do ai platform engineer jobs pay per hour?

As of Sep 15, 2026, the average hourly pay for ai platform engineer in Raleigh, NC is $62.17, according to ZipRecruiter salary data. Most workers in this role earn between $49.09 and $71.73 per hour, depending on experience, location, and employer.

What is an AI Platform Engineer?

AI Platform Engineers are technology professionals who design, build, and maintain the infrastructure that supports the development, deployment, and scaling of artificial intelligence (AI) and machine learning (ML) models. They work closely with data scientists and software engineers to ensure that AI solutions can run efficiently and securely in production environments. Their responsibilities often include managing cloud or on-premises platforms, automating workflows, and implementing best practices for model versioning, monitoring, and resource optimization.

How does an AI Platform Engineer typically collaborate with data scientists and software engineers in a project environment?

AI Platform Engineers often serve as a bridge between data scientists and software engineers, ensuring that machine learning models are seamlessly integrated into scalable, production-ready systems. They work closely with data scientists to understand model requirements and deployment needs, and with software engineers to embed these models within applications and services. This collaboration involves frequent communication, joint troubleshooting, and participation in code reviews to maintain a robust and efficient AI infrastructure.

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

To thrive as an AI Platform Engineer, you need strong programming skills (especially in Python and Java), a background in computer science or related fields, and experience with machine learning frameworks. Familiarity with cloud platforms (like AWS, Azure, or GCP), containerization tools (Docker, Kubernetes), and CI/CD systems is typically required, along with certifications such as Google Cloud Professional Machine Learning Engineer. Excellent problem-solving, collaboration, and communication skills help you integrate AI solutions across teams and projects. These competencies ensure the efficient development, deployment, and maintenance of scalable AI systems in dynamic production environments.

What is the difference between Ai Platform Engineer vs Data Engineer?

AspectAi Platform EngineerData Engineer
CredentialsBachelor's in CS, AI, or related; experience with cloud platformsBachelor's in CS, Data Science, or related; experience with databases and ETL tools
Work EnvironmentDeveloping AI infrastructure, deploying ML models, working with cloud servicesBuilding data pipelines, managing data storage, ensuring data quality
Industry UsageTech companies, AI startups, cloud providersFinance, healthcare, e-commerce, any data-driven industry

While both roles involve working with data and cloud platforms, Ai Platform Engineers focus on building and maintaining AI infrastructure and deploying machine learning models. Data Engineers primarily develop data pipelines and manage data storage. The roles often collaborate but serve different core functions within AI and data ecosystems.

How to become an AI platform engineer?

To become an AI platform engineer, you should have a strong background in computer science, software engineering, or related fields, with expertise in machine learning frameworks, cloud computing, and programming languages like Python or Java. Gaining experience with AI tools, data management, and infrastructure deployment is essential, often supported by certifications in cloud platforms such as AWS or Azure. Building a portfolio of projects and staying updated on AI and DevOps practices can also enhance your qualifications.

What does an AI platform engineer do?

An AI platform engineer designs, develops, and maintains the infrastructure and tools needed to deploy and manage artificial intelligence models at scale. They work with cloud services, programming languages, and machine learning frameworks to ensure efficient model training, deployment, and monitoring in production environments.

What is the salary of AI platform engineer?

The salary of an AI platform engineer typically ranges from $100,000 to $150,000 annually, depending on experience, location, and company size. Senior roles or those with specialized skills in cloud platforms and machine learning may earn higher compensation.

What are popular job titles related to Ai Platform Engineer jobs in Raleigh, NC?

For Ai Platform Engineer jobs in Raleigh, NC, the most frequently searched job titles are:

What job categories do people searching Ai Platform Engineer jobs in Raleigh, NC look for?

The top searched job categories for Ai Platform Engineer jobs in Raleigh, NC are:

What cities near Raleigh, NC are hiring for Ai Platform Engineer jobs?

Cities near Raleigh, NC with the most Ai Platform Engineer job openings:

Ai Platform Engineer jobs near you
Infographic showing various Ai Platform Engineer job openings in Raleigh, NC as of August 2026, with employment types broken down into 57% Full Time, 40% Part Time, and 3% Contract. Highlights an 81% Physical, 2% Hybrid, and 17% Remote job distribution, with an average salary of $129,312 per year, or $62.2 per hour.

Director, AI Engineering

Morrisville, NC • On-site, Remote

WaferWire Cloud Technologies
Software Development • 11 - 50 employees
Learn more about WaferWire Cloud Technologiesexternal

$170K - $180K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

This job post has expired today. Applications are no longer accepted.

Job description

Job Title: Director, AI Engineering
Location: Morrisville, NC
Worksite: Remote
About WCT
WCT is a global talent solutions partner committed to delivering high-impact technology and engineering talent to some of the world's most innovative companies. As a WCT employee, you'll be part of a dynamic, growth-oriented culture that values collaboration, continuous learning, and excellence in execution.
Description and Requirements
About Our Team
  • Client is building Quantum, a next-generation hybrid AI platform that spans Windows, Android, and cloud. As Head of Core Intelligence, you will lead the engineering teams responsible for the "AI brain" of the system - including agentic orchestration, reasoning, fused memory, RAG retrieval, perception models, recommendation systems, and model optimization.
  • You will own the intelligence substrate that powers every AI experience ships across millions of devices. This is a hands-on engineering leadership role, combining deep technical understanding with the ability to operate across multiple layers of the AI stack.
  • We recently introduced Qira, our new cross-device Personal AI that works seamlessly across products.

Location: Remote work in the US is an option with 25% travel.
What You'll Do
  • Build and lead the Core Intelligence organization, owning agentic systems, orchestration, routing, tool frameworks, RAG retrieval, memory, knowledge graph, and perception signals.
  • Architect the intelligence layer for hybrid AI: on-device inference, cloud fallback, multi-model routing, policy enforcement, and context grounding.
  • Drive the development of perception-based triggers, wake-word detection logic, screenshot and audio understanding, OCR/ASR pipelines.
  • Own the recommendation and next-action engines, working closely with Experience Engineering to deliver contextual, proactive AI.
  • Lead the optimization of small and medium models (SLMs): quantization, distillation, pruning, and device-specific tuning.
  • Partner closely with Platform Engineering, Cloud Platform, SRE & Delivery, and Experience teams to ensure Core Intelligence is performant, reliable, and tightly integrated.
  • Define evaluation frameworks and quality gates for intelligence features such as retrieval accuracy, hallucination avoidance, model grounding, and agent reliability.
  • Set the technical direction for the intelligence roadmap, balancing innovation, prototyping, and production reliability.
  • Mentor senior ICs across perception, agentic systems, RAG, memory, and model optimization.
  • Collaborate with research, product, and design teams to bring new agent capabilities and multimodal experiences to life.

Basic Qualifications
  • 12+ years of engineering experience with at least 5 years leading teams in AI/ML systems, agent platforms, search, recommendation, or applied ML infrastructure.
  • Hands-on experience with orchestration frameworks, agentic systems, LLM/SLM pipelines, RAG systems, embeddings, and memory architectures.
  • Strong technical depth in at least one of: perception models (OCR/ASR/vision), retrieval systems, reinforcement learning, model optimization, distributed systems.
  • Experience building systems that run across device + cloud in hybrid or edge environments.

Preferred Qualifications
  • Demonstrated ability to lead senior ICs, set technical direction, and deliver complex AI systems at scale.
  • Strong collaboration skills across platform teams, cloud engineering, UX/experience engineering, and SRE organizations.
  • Ability to thrive in fast-paced, evolving environments and shape the engineering culture for a new AI platform.
  • 25% global travel ability

Compensation / Salary Range: The typical pay range for this role is: USD $170,000/Yearly - $180,000/Yearly. Factors that may affect pay within or outside of this range may include but not limited to geography/market, skills, education, experience, and other qualifications of the successful candidate.
Benefits: Medical, dental, Vision, Life, PTO, Holidays, 401(k) benefits and ancillaries may be available for eligible WCT employees and may vary depending on the nature of your employment.
WCT will accept applications and processes offers for these roles until the role is filled.
Equal Employment Opportunity Declaration:
WCT is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable laws, regulations and ordinances.

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