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Ai Infrastructure Job Jobs in Raleigh, NC (NOW HIRING)

Adopt best engineering practices in automation, HPC and AI/GenAI infrastructure and design patterns * Define and lead technology proof of concepts to ensure feasibility of new data and cloud ...

Job Summary The CI Solutions team builds, validates, and launches NetApp data management, hybrid cloud, FlexPod, and next-generation AI infrastructure solutions. This role serves as a technical ...

We are building the enterprise software infrastructure to capture, catalog, refine, enrich, and protect massive datasets and make them available for real-time data analysis and AI training and ...

We are building the enterprise software infrastructure to capture, catalog, refine, enrich, and protect massive datasets and make them available for real-time data analysis and AI training and ...

The team + the role Pendo's Applied AI team turns AI infrastructure into real business outcomes across Sales, Marketing, and Customer Engineering. AI here isn't a feature we bolt on - it's how we ...

The team + the role Pendo's Applied AI team turns AI infrastructure into real business outcomes across Sales, Marketing, and Customer Engineering. AI here isn't a feature we bolt on - it's how we ...

The team + the role Pendo's Applied AI team turns AI infrastructure into real business outcomes across Sales, Marketing, and Customer Engineering. AI here isn't a feature we bolt on - it's how we ...

Senior Software Engineer

Raleigh, NC · On-site

$95K - $158K/yr

Are you passionate about building scalable AI infrastructure and shaping governance for cutting-edge GenAI solutions? Do you enjoy collaborating across teams while mentoring others and translating ...

Showing results 21-40

Ai Infrastructure Job information

See Raleigh, NC salary details

$27

$57

$84

How much do ai infrastructure job jobs pay per hour?

As of Aug 21, 2026, the average hourly pay for ai infrastructure job in Raleigh, NC is $57.53, according to ZipRecruiter salary data. Most workers in this role earn between $46.73 and $67.07 per hour, depending on experience, location, and employer.

What is an AI infrastructure job?

An AI Infrastructure job involves designing, building, and maintaining the foundational systems and tools required to support artificial intelligence and machine learning workloads. These professionals work on scalable computing environments, manage large datasets, and ensure high-performance computing resources are available for AI development and deployment. Their responsibilities often include optimizing hardware (like GPUs and TPUs), developing cloud-based solutions, and establishing reliable pipelines for data and model management. AI Infrastructure specialists collaborate with data scientists, ML engineers, and IT teams to deliver robust, efficient, and secure platforms that power AI applications.

What are some common challenges faced by professionals working in AI infrastructure roles?

Professionals in AI infrastructure roles often encounter challenges such as ensuring scalability and reliability of systems to handle large volumes of data and compute-intensive workloads. Managing the integration of diverse tools and frameworks, optimizing hardware and cloud resources, and maintaining security and compliance are also critical aspects. Additionally, effective collaboration with data scientists, software engineers, and DevOps teams is essential to streamline AI model deployment and monitoring. Staying current with rapidly evolving technologies is key to overcoming these challenges.

What are the key skills and qualifications needed to thrive in an AI infrastructure role, and why are they important?

To excel in an AI Infrastructure role, you need a strong background in computer science, cloud computing, and distributed systems, often supported by a relevant degree and experience with large-scale data environments. Proficiency with tools like Kubernetes, Docker, TensorFlow, PyTorch, and cloud platforms such as AWS, Azure, or Google Cloud is essential, along with familiarity with CI/CD pipelines and automation frameworks. Strong problem-solving, collaboration, and communication skills help drive innovation and facilitate cross-functional teamwork. These abilities ensure the robust, scalable, and efficient deployment of AI solutions that meet organizational needs.

What is the difference between Ai Infrastructure Job vs Data Engineer?

AspectAi Infrastructure JobData Engineer
Required CredentialsBachelor's in CS, Engineering, or related; knowledge of AI frameworksBachelor's in CS, Data Science, or related; programming skills in SQL, Python
Work EnvironmentData centers, cloud platforms, AI labsData pipelines, cloud environments, database systems
Industry UsageAI development, machine learning deploymentData processing, analytics, data pipeline creation

Ai Infrastructure Jobs focus on building and maintaining the hardware and software systems that support AI applications, including cloud and data center infrastructure. Data Engineers primarily develop and manage data pipelines and storage solutions to enable data analysis and machine learning. While both roles require technical skills and work in tech environments, Ai Infrastructure Jobs are more hardware and system-focused, whereas Data Engineers concentrate on data flow and management.

What are popular job titles related to Ai Infrastructure Job jobs in Raleigh, NC?

For Ai Infrastructure Job jobs in Raleigh, NC, the most frequently searched job titles are:

What job categories do people searching Ai Infrastructure Job jobs in Raleigh, NC look for?

The top searched job categories for Ai Infrastructure Job jobs in Raleigh, NC are:

Infographic showing various Ai Infrastructure Job job openings in Raleigh, NC as of August 2026, with employment types broken down into 87% Full Time, and 13% Contract. Highlights an 49% In-person, 13% Hybrid, and 38% Remote job distribution, with an average salary of $119,666 per year, or $57.5 per hour.

Senior AI Engineer - SFL Scientific

Deloitte

Raleigh, NC

$101K - $139K/yr

Full-time

Re-posted 2 days ago


Deloitte rating

8.2

Company rating: 8.2 out of 10

Based on 92 frontline employees who took The Breakroom Quiz

45th of 151 rated financial services


Job description

Our Deloitte Strategy & Transactions team helps guide clients through their most critical moments and transformational initiatives. From strategy to execution, this team delivers integrated, end-to-end support and advisory services covering valuation modeling, cost optimization, restructuring, business design and transformation, infrastructure and real estate, mergers and acquisitions (M&A), and sustainability. Work alongside clients every step of the way, helping them navigate new challenges, avoid financial pitfalls, and provide practical solutions at every stage of their journey-before, during, and after any major transformational projects or transactions.
Are you eager to shape the future of emerging technologies? Imagine joining an acclaimed team where career paths span from account executives and data scientists to AI strategists, machine learning specialists, and data engineers. SFL Scientific, a Deloitte Business, is looking to add a Senior AI Engineer to their vibrant environment. SFL Scientific is part of our broader Strategy Offering within the Strategy & Transactions practice, whose specialized team brings together key capabilities to design integrated solutions that drive transformational change for our clients. Take the next step in your technical journey-develop your leadership, consulting acumen, and reputation as a trailblazer within the AI engineering field by joining our team!

Recruiting for this role ends on 8/31/2026.

Work You'll Do
As a Senior AI Engineer, you'll work cross-functionally with data scientists, machine learning engineers, project managers, and industry experts to develop robust AI infrastructure and deployment services for our novel machine learning applications. Key to this role is the ability to demonstrate both traditional data engineering expertise, leveraging cloud/enterprise/open-source solutions, and constructing IT infrastructure for organizations across a wide variety of industries.

In our consultative approach, we are platform agnostic and committed to providing the best technical solutions for each client and solution. Our engineering team leverages emerging technologies and best practices across data security, documentation, cloud services and engineering architecture to create solutions and products that address complex issues and business problems faced by global organizations. Some of our novel use cases include cancer detection, drug discovery, optimizing population health and clinical trials, autonomous systems and edge AI, and renewable energy. Key responsibilities:

  • Work with clients to design, develop, and deploy new architectures to support machine learning & automation applications
  • Leverage advanced technical skills in modern data architecture, data science engineering, data transformation, and management of structured and unstructured data sources using cloud computing or on-prem technologies
  • Design and lead development on scalable, high-performance data architecture solutions that supports both the client business as well as AI/GenAI use cases
  • Support and enhance data architecture, and data pipelines, and define database schemas (Graph, SQL, NoSQL) to develop algorithm scalability and deployment based on agile business priorities and initiatives
  • Participate in architectural and deployment discussions to ensure solutions are designed for successful scale, security, and high availability in the cloud or on prem
  • Adopt best engineering practices in automation, HPC and AI/GenAI infrastructure and design patterns
  • Define and lead technology proof of concepts to ensure feasibility of new data and cloud technology solutions
  • Display strong thought leadership and execution in pursuit of modern data architecture principles and technology modernization
  • Mentor, motivate, and coach junior members on technical best practices and inspire professional development

A successful candidate would possess these skills:

  • Ability to work independently and collaborate as part of a team
  • Effective written and verbal communication skills
  • Meticulous attention to detail and quality of work product
  • Ability to build and sustain professional relationships
  • Ability to lead projects or workstreams
  • Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
  • Strong interpersonal skills and professional demeanor
  • Ability to meet deadlines
  • Ability to provide clear guidance to others

The Team

Our Strategy offering architects bold strategies to achieve business and mission goals, enabling growth, competitive advantage, technology modernization, and continuous digital and AI transformation.
Specifically, SFL Scientific, a Deloitte Business, is a data science professional services practice focused on strategy, technology, and solving business challenges with Artificial Intelligence (AI). The team has a proven track record serving large, market-leading organizations in the private and public sectors, successfully delivering high-quality, novel and complex projects, and offering deep domain and scientific capabilities. Made up of experienced AI strategists, data scientists, and AI engineers, they serve as trusted advisors to executives, helping them understand and evaluate new and essential areas for AI investment and identify unique opportunities to transform their businesses.
Qualifications

Required:

  • Bachelor's degree in a STEM field (Computer Science, Engineering, Physics, etc.) or equivalent experience
  • 4+ years of experience working in data engineering, data science, software engineering, MLOps specializing in AI and Machine Learning deployment
  • 4+ years of experience in designing cloud solutions and supporting production projects, including hands-on experience with AWS services (or Azure, GCP equivalents)
  • 4+ years of programming experience with Linux Shell/CLI, Python, SQL, PowerShell, etc.
  • 2+ years of experience managing teams in technical delivery and delivering complex and critical projects
  • 2+ years of experience in DevOps and leveraging CI/CD services: Puppet, Ansible, Chef, Airflow, Terraform, Jenkins
  • 2+ years of experience with database development and ETL/ELT pipelines (relational, NoSQL, Neo4j)
  • 2+ years of experience with deployment and optimization: Kubernetes, Docker, NVIDIA TensorRT/Triton, RAPIDs, Kubeflow, MLflow, Kafka, etc.
  • Live within commuting distance to one of Deloitte's consulting offices
  • Ability to travel 10%, on average, based on the work you do and the clients and industries/sectors you serve
  • Limited immigration sponsorship may be available

Preferred:

  • Master's degree in Computer Science, Engineering, Physics, etc. or related STEM field
  • AWS/Azure Certifications (AWS/Azure Certified: SysOps Administrator, DevOps Engineer, Solutions Architect)
  • 2+ years of experience with GPU computing (CUDA, OpenCL) and HPC system software stack

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $128,000 to $252,500.

You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

Qualifications:

Our Deloitte Strategy & Transactions team helps guide clients through their most critical moments and transformational initiatives. From strategy to execution, this team delivers integrated, end-to-end support and advisory services covering valuation modeling, cost optimization, restructuring, business design and transformation, infrastructure and real estate, mergers and acquisitions (M&A), and sustainability. Work alongside clients every step of the way, helping them navigate new challenges, avoid financial pitfalls, and provide practical solutions at every stage of their journey-before, during, and after any major transformational projects or transactions.
Are you eager to shape the future of emerging technologies? Imagine joining an acclaimed team where career paths span from account executives and data scientists to AI strategists, machine learning specialists, and data engineers. SFL Scientific, a Deloitte Business, is looking to add a Senior AI Engineer to their vibrant environment. SFL Scientific is part of our broader Strategy Offering within the Strategy & Transactions practice, whose specialized team brings together key capabilities to design integrated solutions that drive transformational change for our clients. Take the next step in your technical journey-develop your leadership, consulting acumen, and reputation as a trailblazer within the AI engineering field by joining our team!

Recruiting for this role ends on 8/31/2026.

Work You'll Do
As a Senior AI Engineer, you'll work cross-functionally with data scientists, machine learning engineers, project managers, and industry experts to develop robust AI infrastructure and deployment services for our novel machine learning applications. Key to this role is the ability to demonstrate both traditional data engineering expertise, leveraging cloud/enterprise/open-source solutions, and constructing IT infrastructure for organizations across a wide variety of industries.

In our consultative approach, we are platform agnostic and committed to providing the best technical solutions for each client and solution. Our engineering team leverages emerging technologies and best practices across data security, documentation, cloud services and engineering architecture to create solutions and products that address complex issues and business problems faced by global organizations. Some of our novel use cases include cancer detection, drug discovery, optimizing population health and clinical trials, autonomous systems and edge AI, and renewable energy. Key responsibilities:

  • Work with clients to design, develop, and deploy new architectures to support machine learning & automation applications
  • Leverage advanced technical skills in modern data architecture, data science engineering, data transformation, and management of structured and unstructured data sources using cloud computing or on-prem technologies
  • Design and lead development on scalable, high-performance data architecture solutions that supports both the client business as well as AI/GenAI use cases
  • Support and enhance data architecture, and data pipelines, and define database schemas (Graph, SQL, NoSQL) to develop algorithm scalability and deployment based on agile business priorities and initiatives
  • Participate in architectural and deployment discussions to ensure solutions are designed for successful scale, security, and high availability in the cloud or on prem
  • Adopt best engineering practices in automation, HPC and AI/GenAI infrastructure and design patterns
  • Define and lead technology proof of concepts to ensure feasibility of new data and cloud technology solutions
  • Display strong thought leadership and execution in pursuit of modern data architecture principles and technology modernization
  • Mentor, motivate, and coach junior members on technical best practices and inspire professional development

A successful candidate would possess these skills:

  • Ability to work independently and collaborate as part of a team
  • Effective written and verbal communication skills
  • Meticulous attention to detail and quality of work product
  • Ability to build and sustain professional relationships
  • Ability to lead projects or workstreams
  • Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
  • Strong interpersonal skills and professional demeanor
  • Ability to meet deadlines
  • Ability to provide clear guidance to others

The Team

Our Strategy offering architects bold strategies to achieve business and mission goals, enabling growth, competitive advantage, technology modernization, and continuous digital and AI transformation.
Specifically, SFL Scientific, a Deloitte Business, is a data science professional services practice focused on strategy, technology, and solving business challenges with Artificial Intelligence (AI). The team has a proven track record serving large, market-leading organizations in the private and public sectors, successfully delivering high-quality, novel and complex projects, and offering deep domain and scientific capabilities. Made up of experienced AI strategists, data scientists, and AI engineers, they serve as trusted advisors to executives, helping them understand and evaluate new and essential areas for AI investment and identify unique opportunities to transform their businesses.
Qualifications

Required:

  • Bachelor's degree in a STEM field (Computer Science, Engineering, Physics, etc.) or equivalent experience
  • 4+ years of experience working in data engineering, data science, software engineering, MLOps specializing in AI and Machine Learning deployment
  • 4+ years of experience in designing cloud solutions and supporting production projects, including hands-on experience with AWS services (or Azure, GCP equivalents)
  • 4+ years of programming experience with Linux Shell/CLI, Python, SQL, PowerShell, etc.
  • 2+ years of experience managing teams in technical delivery and delivering complex and critical projects
  • 2+ years of experience in DevOps and leveraging CI/CD services: Puppet, Ansible, Chef, Airflow, Terraform, Jenkins
  • 2+ years of experience with database development and ETL/ELT pipelines (relational, NoSQL, Neo4j)
  • 2+ years of experience with deployment and optimization: Kubernetes, Docker, NVIDIA TensorRT/Triton, RAPIDs, Kubeflow, MLflow, Kafka, etc.
  • Live within commuting distance to one of Deloitte's consulting offices...

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