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$36.5K

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$140K

How much do intelligent systems jobs pay per year?

As of Jul 27, 2026, the average yearly pay for intelligent systems in the United States is $89,782.00, according to ZipRecruiter salary data. Most workers in this role earn between $69,000.00 and $112,000.00 per year, depending on experience, location, and employer.

What are some common challenges faced by professionals working in Intelligent Systems roles, and how can they be addressed?

Professionals in Intelligent Systems often encounter challenges such as integrating AI solutions with legacy systems, ensuring data quality for machine learning models, and keeping up with rapid advancements in technology. Collaboration with cross-functional teams—including data scientists, engineers, and domain experts—is key to overcoming these hurdles. Staying proactive through continuous learning and participating in industry forums or trainings also helps professionals remain effective and innovative in this evolving field.

What is a $900000 AI job?

A $900,000 AI job typically refers to a high-level position in artificial intelligence, such as a senior AI researcher, machine learning director, or chief AI officer, often found in large tech companies or specialized firms. These roles usually require advanced skills in programming, data analysis, and AI frameworks, along with significant experience and leadership responsibilities.

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

To thrive as an Intelligent Systems Engineer, you need a solid background in computer science or engineering, proficiency in machine learning algorithms, and strong analytical skills, usually backed by a relevant degree. Familiarity with programming languages like Python or C++, knowledge of AI frameworks (such as TensorFlow or PyTorch), and experience with embedded systems or robotics platforms are typically required. Creative problem-solving, adaptability, and effective communication help professionals excel in interdisciplinary teams and innovative environments. These skills are essential for designing, implementing, and optimizing intelligent systems that solve complex real-world problems.

What is the difference between Intelligent Systems vs Data Analysts?

AspectIntelligent SystemsData Analysts
Required CredentialsBachelor's or higher in Computer Science, Engineering, or related fieldsBachelor's or higher in Statistics, Mathematics, or related fields
Work EnvironmentTech companies, research labs, AI development firmsBusiness, finance, healthcare, and marketing sectors
Employer & Industry UsageUsed in AI, automation, robotics, and software developmentUsed in data interpretation, reporting, and decision-making

Intelligent Systems focus on designing and developing AI-driven solutions, while Data Analysts interpret data to support business decisions. Both roles require analytical skills but differ in technical complexity and application areas.

What are intelligent systems?

Intelligent systems are advanced computer-based systems that can perceive, reason, learn, and act autonomously or semi-autonomously in complex environments. These systems often use artificial intelligence (AI), machine learning, and data analytics to solve problems, make decisions, and adapt to new information. Examples include self-driving cars, smart home devices, robotics, and speech recognition systems. Intelligent systems are widely used in industries such as healthcare, manufacturing, transportation, and finance to enhance efficiency and innovation.

What are some examples of intelligent systems?

Intelligent systems are computer-based systems that use artificial intelligence techniques to mimic human decision-making and problem-solving. Examples include expert systems, which simulate human expertise; autonomous vehicles that navigate and make driving decisions; and recommendation systems used by online platforms to personalize content. These systems often incorporate machine learning, natural language processing, and data analysis to improve performance over time.

What is an intelligent systems engineering salary?

An intelligent systems engineering salary varies based on experience, education, and location, but typically ranges from $80,000 to $130,000 annually in the United States. Professionals in this field often have skills in machine learning, robotics, and software development, with higher salaries for those with advanced certifications or specialized expertise.

Which 3 jobs will survive AI?

In the field of Intelligent Systems, jobs such as AI system engineers, data scientists, and cybersecurity specialists are expected to remain in demand due to their reliance on complex problem-solving, domain expertise, and the need for human oversight. These roles require advanced technical skills, critical thinking, and adaptability that are difficult for AI to fully replicate. Continuous learning and certification in relevant tools like machine learning frameworks can enhance job security in these areas.
More about Intelligent Systems jobs
What states have the most Intelligent Systems jobs? States with the most job openings for Intelligent Systems jobs include:
What job categories do people searching Intelligent Systems jobs look for? The top searched job categories for Intelligent Systems jobs are:
Intelligent Systems jobs near you
Infographic showing various Intelligent Systems job openings in the United States as of July 2026, with employment types broken down into 1% As Needed, 90% Full Time, 8% Part Time, and 1% Contract. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution, with an average salary of $89,782 per year, or $43.2 per hour.
Intelligent Systems Engineer II

Intelligent Systems Engineer II

ClarkDietrich

West Chester, OH • On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 5 days ago

ClarkDietrich rating

7.6

Company rating: 7.6 out of 10

Based on 5 frontline employees who took The Breakroom Quiz

Job description

Do you have a strong work ethic and the desire to join an organization that invests in its people through cross-training and development? ClarkDietrich fosters a work-life balance and offers competitive compensation and benefits. Join the ClarkDietrich team by applying to the Intelligent Systems Engineer II position.
Position Summary
The Intelligent Systems Engineer II will support the design, development, testing, and implementation of intelligent software systems that combine artificial intelligence, machine learning, data engineering, automation, cloud services, and modern software development practices.
This role is a hands-on technical engineering position. The Intelligent Systems Engineer II will work under the direction of the Technical Manager and will be responsible for solving assigned technical problems, contributing to system design and implementation, building reliable components, and supporting the development of scalable intelligent applications.
This position is not expected to independently define business problems, own business-facing strategy, or directly lead stakeholder discovery. Instead, the role will translate technical direction, requirements, and priorities provided by the Technical Manager into practical engineering solutions.
Role Scope and Expectations
  • Work primarily as a technical contributor under the direction of the Technical Manager.
  • Solve assigned technical problems at the system, software, data, AI, and integration levels.
  • Support implementation, testing, documentation, and production-readiness of intelligent systems.
  • Escalate risks, blockers, tradeoffs, and unclear requirements to the Technical Manager in a timely manner.
  • Participate in technical discussions and provide input, while business-facing prioritization and solution direction remain coordinated through the Technical Manager or designated leadership.

Key Responsibilities
Intelligent Systems Development
  • Design, develop, test, and maintain components of AI-enabled software systems and automation workflows.
  • Build technical solutions using machine learning models, large language models, data pipelines, APIs, databases, and cloud services.
  • Implement assigned features, services, integrations, and backend logic based on technical direction from the Technical Manager.
  • Support prototype development, technical validation, and transition of approved solutions into stable, production-ready implementations.
  • Research and evaluate technologies when assigned, and provide technical findings and recommendations to the Technical Manager.

Machine Learning and Applied AI
  • Support the development, testing, evaluation, and improvement of machine learning and AI-enabled solutions.
  • Assist with model training, validation, performance testing, accuracy measurement, and error analysis.
  • Prepare and process structured, semi-structured, and unstructured data for use in intelligent systems.
  • Help create evaluation methods to measure consistency, reliability, accuracy, and technical performance.
  • Work with the Technical Manager to ensure AI outputs are reviewed, explainable where needed, and aligned with approved technical standards.

Data Engineering and System Integration
  • Build and maintain data pipelines for collecting, cleaning, transforming, and organizing technical and operational data.
  • Develop backend services, APIs, and integration components that connect intelligent systems with internal applications.
  • Support data quality, traceability, security, and maintainability across assigned technical work.
  • Work with databases, file storage, cloud services, and application interfaces as needed.
  • Document data flows, integration logic, assumptions, and technical limitations.

Cloud and Software Engineering
  • Develop cloud-supported applications and services using modern software engineering practices.
  • Participate in version control, code reviews, testing, deployment, environment management, and release support.
  • Support CI/CD pipelines, containerization, automated testing, and monitoring where applicable.
  • Improve performance, reliability, scalability, maintainability, and cost efficiency of assigned systems.
  • Follow team standards for code quality, documentation, security, and operational support.

Collaboration and Technical Execution
  • Work under the leadership of the Technical Manager to execute assigned technical priorities.
  • Collaborate with software developers, engineers, data contributors, product contributors, interns, and IT stakeholders as needed.
  • Ask clarifying technical questions and raise risks, blockers, and tradeoffs early.
  • Participate in design reviews, technical planning sessions, and implementation discussions.
  • Provide clear status updates, technical notes, and documentation for assigned work.

Required Qualifications
  • Degree or equivalent experience in computer science, engineering, artificial intelligence, machine learning, data science, software engineering, or a related technical field.
  • Strong programming skills, preferably in Python and modern backend development.
  • Experience with applied AI, machine learning, data processing, automation, or intelligent software systems.
  • Experience working with APIs, databases, backend services, and software integrations.
  • Familiarity with cloud platforms, preferably AWS.
  • Understanding of software engineering practices, including version control, testing, documentation, and deployment.
  • Ability to understand technical direction and convert it into working software components.
  • Strong analytical, problem-solving, communication, and collaboration skills.
  • Ability to work in a structured technical team environment under the guidance of a Technical Manager.

Preferred Qualifications
  • Advanced degree or research experience in artificial intelligence, machine learning, engineering, optimization, data science, or computational methods.
  • Experience with large language models, OCR, retrieval-augmented generation, vector databases, intelligent agents, or document intelligence systems.
  • Experience applying AI or machine learning to engineering, construction, manufacturing, automation, or complex operational workflows.
  • Experience with AWS services such as S3, Lambda, ECS, ECR, API Gateway, RDS, DynamoDB, Bedrock, Textract, SageMaker, or similar technologies.
  • Experience with CI/CD, GitHub, containers, automated testing, and modern software release practices.
  • Familiarity with technical design workflows, engineering software, or knowledge-intensive business processes is a plus.

Key Success Outcomes
  • Deliver assigned technical components for intelligent systems and AI-enabled applications.
  • Support data pipelines, model evaluation, backend services, APIs, and cloud-based implementation work.
  • Contribute to improving system reliability, maintainability, performance, and scalability.
  • Follow technical direction from the Technical Manager and execute work with increasing independence.
  • Communicate progress, risks, and technical findings clearly and consistently.
  • Help strengthen the team's software, data, AI, and cloud engineering practices.

Reporting and Collaboration
This role reports to the Technical Manager within the software development or digital technology function.
The position is primarily responsible for hands-on technical execution and implementation.
Business requirements, stakeholder priorities, and solution direction will be coordinated through the Technical Manager or designated leadership.
CLARKDIETRICH BENEFITS INCLUDE:
Full benefits package (Medical, Dental, Vision, Flexible Spending Accounts and Life Insurance)
401(k) with company match
Annual Incentive
Paid Time Off
Tuition Reimbursement
Professional Certification Reimbursement Program
Community Service Day

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