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Ai Coder Jobs in Nevada (NOW HIRING)

PB Coding Coordinator

Carson City, NV · On-site

$31.01 - $48.84/hr

Required credential: CPC Certified Professional Coder (CPC) or Certified Coding Specialist ... At Intermountain Health, we use the artificial intelligence ("AI") platform, HiredScore to improve ...

You can take a vague request and turn it into a clear, testable spec before writing any code.You check AI quality with test sets and criteria, not just by eyeballing a few outputs.You know LLMs fail ...

You can take a vague request and turn it into a clear, testable spec before writing any code. * You check AI quality with test sets and criteria, not just by eyeballing a few outputs. * You know LLMs ...

You can take a vague request and turn it into a clear, testable spec before writing any code. * You check AI quality with test sets and criteria, not just by eyeballing a few outputs. * You know LLMs ...

Showing results 21-40

Ai Coder information

See Nevada salary details

$16

$27

$44

How much do ai coder jobs pay per hour?

As of Sep 7, 2026, the average hourly pay for ai coder in Nevada is $27.99, according to ZipRecruiter salary data. Most workers in this role earn between $19.33 and $35.24 per hour, depending on experience, location, and employer.

What is an AI coder?

AI Coders are professionals who develop, implement, and maintain artificial intelligence (AI) systems and applications. They use programming languages such as Python, Java, and R to write code that enables machines to perform tasks that typically require human intelligence, such as learning, reasoning, and problem-solving. AI Coders often work with machine learning models, neural networks, and large datasets to create intelligent solutions for various industries. Their work can range from building chatbots and recommendation systems to designing complex algorithms for automation.

What types of projects do AI coders typically work on, and how does project collaboration usually happen?

AI Coders are often involved in developing machine learning models, creating data pipelines, and integrating AI solutions into existing products. Collaboration is a key part of the role, with AI Coders working closely with data scientists, software engineers, and product managers to translate business needs into technical solutions. Most teams use agile methodologies, daily stand-ups, and collaborative platforms like GitHub or Jira to coordinate tasks and track progress. This structure ensures that AI Coders receive frequent feedback and can contribute ideas throughout the development cycle.

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

To thrive as an AI Coder, you need strong programming skills (especially in Python), a solid understanding of machine learning concepts, and typically a degree in computer science or a related field. Familiarity with AI frameworks like TensorFlow or PyTorch, as well as experience with version control systems such as Git, is essential. Strong problem-solving abilities, attention to detail, and effective communication help you collaborate with teams and explain complex solutions. These skills and qualities are crucial for developing, optimizing, and maintaining reliable AI models that address real-world challenges.

What is the difference between Ai Coder vs Data Scientist?

AspectAi CoderData Scientist
Required CredentialsProgramming skills, knowledge of AI frameworks, certifications in AI/MLStatistics, programming, data analysis certifications
Work EnvironmentSoftware development teams, AI research labsData analysis teams, research environments
Employer & Industry UsageTech companies, AI startups, R&D departmentsFinance, healthcare, marketing, tech firms

While both roles involve working with data and algorithms, Ai Coders primarily focus on developing AI models and coding AI solutions, whereas Data Scientists analyze data to extract insights and inform business decisions. Ai Coders are more involved in software development, while Data Scientists emphasize statistical analysis and data interpretation.

How do you become an AI coder?

To become an AI coder, you typically need a strong foundation in programming languages such as Python or Java, along with knowledge of machine learning frameworks like TensorFlow or PyTorch. Earning a degree in computer science, data science, or a related field and gaining experience through projects or internships are common steps. Developing skills in algorithms, data structures, and mathematics is also essential for working effectively in AI development.

How much do AI coders make?

AI coders, also known as artificial intelligence programmers, typically earn between $80,000 and $150,000 annually, depending on experience, location, and industry. Senior roles or those with specialized skills in machine learning and deep learning can earn higher salaries, especially in tech hubs or large companies.

What are popular job titles related to Ai Coder jobs in Nevada?

For Ai Coder jobs in Nevada, the most frequently searched job titles are:

What cities in Nevada are hiring for Ai Coder jobs?

Cities in Nevada with the most Ai Coder job openings:

Infographic showing various Ai Coder job openings in Nevada as of August 2026, with employment types broken down into 77% Full Time, 20% Part Time, and 3% Contract. Highlights an 70% Physical, 3% Hybrid, and 27% Remote job distribution, with an average salary of $58,229 per year, or $28 per hour.

AI Security Engineer Manager

Deloitte

Las Vegas, NV

Full-time

Re-posted 13 hours ago


Key responsibilities

  • Design and deliver AI-enabled solutions that are secure by design, balancing business value with risk mitigation.

  • Actively contribute to architecture, design, and development of AI/ML and GenAI systems with embedded security controls.

  • Identify and address AI-specific vulnerabilities, including prompt injection, data leakage, model manipulation, and misuse.


Deloitte rating

8.2

Company rating: 8.2 out of 10

Based on 93 frontline employees who took The Breakroom Quiz

48th of 154 rated financial services


Job description

As a Manager in AI Security Engineering, you will play a critical role in securing the development and deployment of AI/ML and Generative AI solutions. You will operate hands-on across high-visibility initiatives, embedding security, trust, and resilience into AI systems while enabling rapid, responsible innovation.

Recruiting for this role ends on 9/19/2026.

Work you'll do

You will bring strong engineering depth and applied AI knowledge, combined with expertise in cybersecurity principles, to design and deliver secure, scalable solutions. This role requires a collaborative, execution-focused leader who can influence teams, mentor engineers, and ensure AI systems meet enterprise security, risk, and compliance expectations.

Key Responsibilities

Secure, Outcome-Driven Delivery
Design and deliver AI-enabled solutions that are secure by design, balancing business value with risk mitigation. Solve complex problems while ensuring protection of data, models, and systems.

Hands-On AI Security Engineering
Actively contribute to architecture, design, and development of AI/ML and GenAI systems with embedded security controls. Integrate security across the SSDLC, including code reviews, testing, and deployment. In this role you will be responsible for managing AI defensive technologies and the operations of those technologies which will evolve over time.

AI Risk Identification and Mitigation
Identify and address AI-specific vulnerabilities, including prompt injection, data leakage, model manipulation, and misuse. Implement practical safeguards to ensure system integrity and trustworthiness.

Technical Leadership and Advocacy
Serve as a trusted technical voice for secure AI engineering. Ensure solutions are feasible, secure, and aligned with business and customer objectives.

Engineering Excellence with Security Focus
Maintain high standards for code quality, scalability, and security. Contribute to secure coding practices, reusable patterns, and continuous improvement across engineering teams.

Iterative and Responsible Innovation
Support rapid experimentation while applying appropriate security guardrails. Enable teams to innovate safely through controlled, risk-aware development practices.

Cross-Functional Collaboration
Partner closely with product, engineering, cybersecurity, and risk teams to embed AI security into solutions. Balance usability, performance, and security in decision-making.

Standards and Best Practices
Apply and help evolve standards for AI security, including data protection, access control, model validation, and monitoring within DevSecOps and MLOps pipelines.

Communication and Influence
Clearly articulate technical risks, trade-offs, and solutions to both technical and non-technical stakeholders. Contribute to alignment and informed decision-making.

Impact

This role directly contributes to reducing enterprise risk and strengthening trust in AI systems. Your work will enable secure adoption of AI capabilities while protecting critical assets and maintaining compliance.

The 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 mentor and provide clear guidance to others

The team

Deloitte Technology US (DT - US) helps power Deloitte's success, which serves many of the world's largest, most respected organizations. We develop and deploy cutting-edge internal and go-to-market solutions that help Deloitte operate effectively and lead in the market. Our reputation is built on a tradition of delivering with excellence.

The ~3,000 professionals in DT - US deliver services including:

  • Cyber Security
  • Technology Support
  • Technology & Infrastructure
  • Applications
  • Relationship Management
  • Strategy & Communications
  • Project Management
  • Financials

Cyber Security

Cyber Security vigilantly protects Deloitte and client data. The team leads a strategic cyber risk program that adapts to a rapidly changing threat landscape, changes in business strategies, risks, and vulnerabilities. Using situational awareness, threat intelligence, and building a security culture across the organization, the team helps to protect the Deloitte brand.

Areas of focus include:

  • Risk & Compliance
  • Identity & Access Management
  • Data Protection
  • Cyber Design
  • Incident Response
  • Security Architecture
  • Business Partnership

Qualifications

Required:

  • Bachelor's degree or equivalent in Computer Science, Computer Engineering, Business Administration
  • Minimum 6 years of relevant experience in software engineering, cybersecurity, and/or including AI/ML, with hands-on delivery experience
  • Minimum 1 year of people and/or process management experience

Preferred:

  • Strong understanding of AI/GenAI technologies and associated security risks (e.g., prompt injection, data exposure, adversarial threats)
  • Experience building and securing applications using Python, JavaScript, or similar, along with ML frameworks (e.g., PyTorch, TensorFlow)
  • Familiarity with secure development practices (DevSecOps) and integrating security into CI/CD and MLOps pipelines
  • Experience with cloud platforms (AWS, Azure, GCP) and cloud-native security principles
  • Knowledge of data protection, identity/access management, and secure architecture patterns
  • Ability to work across teams, mentor engineers, and contribute to a strong engineering culture
  • Strong communication skills with the ability to translate technical concepts into business-relevant insights

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 $118,700 to $243,700.  

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. 

EA_ExpHire
RITM10427821

Qualifications:

As a Manager in AI Security Engineering, you will play a critical role in securing the development and deployment of AI/ML and Generative AI solutions. You will operate hands-on across high-visibility initiatives, embedding security, trust, and resilience into AI systems while enabling rapid, responsible innovation.

Recruiting for this role ends on 9/19/2026.

Work you'll do

You will bring strong engineering depth and applied AI knowledge, combined with expertise in cybersecurity principles, to design and deliver secure, scalable solutions. This role requires a collaborative, execution-focused leader who can influence teams, mentor engineers, and ensure AI systems meet enterprise security, risk, and compliance expectations.

Key Responsibilities

Secure, Outcome-Driven Delivery
Design and deliver AI-enabled solutions that are secure by design, balancing business value with risk mitigation. Solve complex problems while ensuring protection of data, models, and systems.

Hands-On AI Security Engineering
Actively contribute to architecture, design, and development of AI/ML and GenAI systems with embedded security controls. Integrate security across the SSDLC, including code reviews, testing, and deployment. In this role you will be responsible for managing AI defensive technologies and the operations of those technologies which will evolve over time.

AI Risk Identification and Mitigation
Identify and address AI-specific vulnerabilities, including prompt injection, data leakage, model manipulation, and misuse. Implement practical safeguards to ensure system integrity and trustworthiness.

Technical Leadership and Advocacy
Serve as a trusted technical voice for secure AI engineering. Ensure solutions are feasible, secure, and aligned with business and customer objectives.

Engineering Excellence with Security Focus
Maintain high standards for code quality, scalability, and security. Contribute to secure coding practices, reusable patterns, and continuous improvement across engineering teams.

Iterative and Responsible Innovation
Support rapid experimentation while applying appropriate security guardrails. Enable teams to innovate safely through controlled, risk-aware development practices.

Cross-Functional Collaboration
Partner closely with product, engineering, cybersecurity, and risk teams to embed AI security into solutions. Balance usability, performance, and security in decision-making.

Standards and Best Practices
Apply and help evolve standards for AI security, including data protection, access control, model validation, and monitoring within DevSecOps and MLOps pipelines.

Communication and Influence
Clearly articulate technical risks, trade-offs, and solutions to both technical and non-technical stakeholders. Contribute to alignment and informed decision-making.

Impact

This role directly contributes to reducing enterprise risk and strengthening trust in AI systems. Your work will enable secure adoption of AI capabilities while protecting critical assets and maintaining compliance.

The 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 mentor and provide clear guidance to others

The team

Deloitte Technology US (DT - US) helps power Deloitte's success, which serves many of the world's largest, most respected organizations. We develop and deploy cutting-edge internal and go-to-market solutions that help Deloitte operate effectively and lead in the market. Our reputation is built on a tradition of delivering with excellence.

The ~3,000 professionals in DT - US deliver services including:

  • Cyber Security
  • Technology Support
  • Technology & Infrastructure
  • Applications
  • Relationship Management
  • Strategy & Communications
  • Project Management
  • Financials

Cyber Security

Cyber Security vigilantly protects Deloitte and client data. The team leads a strategic cyber risk program that adapts to a rapidly changing threat landscape, changes in business strategies, risks, and vulnerabilities. Using situational awareness, threat intelligence, and building a security culture across the organization, the team helps to protect the Deloitte brand.

Areas of focus include:

  • Risk & Compliance
  • Identity & Access Management
  • Data Protection
  • Cyber Design
  • Incident Response
  • Security Architecture
  • Business Partnership

Qualifications

Required:

  • Bachelor's degree or equivalent in Computer Science, Computer Engineering, Business Administration
  • Minimum 6 years of relevant experience in software engineering, cybersecurity, and/or including AI/ML, with hands-on delivery experience
  • Minimum 1 year of people and/or process management experience

Preferred:

  • Strong understanding of AI/GenAI technologies and associated security risks (e.g., prompt injection, data exposure, adversarial threats)
  • Experience building and securing applications using Python, JavaScript, or similar, along with ML frameworks (e.g., PyTorch, TensorFlow)
  • Familiarity with secure development practices (DevSecOps) and integrating security into CI/CD and MLOps pipelines
  • Experience with cloud platforms (AWS, Azure, GCP) and cloud-native security principles
  • Knowledge of data protection, identity/access management, and secure architecture patterns
  • Ability to work across teams, mentor engineers, and contribute to a strong engineering culture
  • Strong communication skills with the ability to translate technical concepts into business-relevant insights

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. A...


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