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Ai In Jobs in Iowa (NOW HIRING)

Cennox

Field Technician

Davenport, IA · On-site

$18.75 - $25.50/hr

Notice on Use of AI in Hiring As part of our commitment to fair and efficient hiring practices, Cennox uses JazzHR's TalentFit AI tool to assist in evaluating candidate applications. This technology ...

Cennox

Field Technician

Davenport, IA · On-site

$18.75 - $25.50/hr

Notice on Use of AI in Hiring As part of our commitment to fair and efficient hiring practices, Cennox uses JazzHR's TalentFit AI tool to assist in evaluating candidate applications. This technology ...

Berkley

AI Technology Leader

Urbandale, IA · On-site

As part of our enterprise transformation, we are investing in next-generation AI technologies to reimagine how we operate, serve customers, and manage risk. Responsibilities We are seeking a ...

Berkley

AI Technology Leader

Urbandale, IA · On-site

As part of our enterprise transformation, we are investing in next-generation AI technologies to reimagine how we operate, serve customers, and manage risk. Responsibilities We are seeking a ...

Berkley

AI Technology Leader

Urbandale, IA · On-site

As part of our enterprise transformation, we are investing in next-generation AI technologies to reimagine how we operate, serve customers, and manage risk. We are seeking a strategic, enterprise ...

Fundraise Up

Sr. Solutions Consultant

Estherville, IA · Remote

We expect every team member to actively use AI in their day-to-day work, identify where AI can change the shape of problems in their function, and grow their fluency as the tools evolve. You should ...

Eliassen Group

Technical Project Manager

Des Moines, IA · On-site +1

$50 - $62/hr

The use of AI in our process is intended to support fairness, efficiency, and consistency, and Eliassen Group takes measures to prevent bias or discrimination in connection with its hiring practices.

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Ai In information

What is an AI Engineer?

An AI Engineer is a professional who designs, develops, and implements artificial intelligence systems and applications. They use machine learning algorithms, deep learning frameworks, and data analysis techniques to create intelligent solutions that can perform tasks such as image recognition, natural language processing, and decision-making. AI Engineers often collaborate with data scientists and software developers to build models, train AI systems, and deploy them in real-world environments. Their work is crucial in advancing automation and making technology smarter across various industries.

What is the difference between Ai In vs Data Analyst?

AspectAi InData Analyst
Required CredentialsTypically a degree in AI, computer science, or related field; certifications in AI or machine learningDegree in statistics, mathematics, or related field; certifications in data analysis or visualization
Work EnvironmentTech companies, AI research labs, startups; focus on developing AI modelsBusiness, finance, healthcare sectors; analyze data to inform decisions
Employer & Industry UsagePrimarily in tech and AI-focused industriesAcross various industries including finance, healthcare, marketing

While both roles involve working with data, Ai In focuses on developing and implementing AI models, whereas Data Analysts interpret data to support business decisions. Ai In roles require specialized knowledge in AI and machine learning, while Data Analysts focus on data visualization and statistical analysis.

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

To thrive as an AI Engineer, you need strong programming skills (especially in Python), a solid foundation in mathematics and statistics, and typically a degree in computer science, engineering, or a related field. Familiarity with machine learning frameworks like TensorFlow or PyTorch, experience with data modeling, and sometimes certifications in AI or data science are highly valued. Critical thinking, creativity, and effective communication help AI Engineers collaborate on complex projects and translate technical concepts for diverse audiences. These skills and qualities are crucial for developing innovative, reliable AI solutions that address real-world challenges.

What are some common challenges AI Engineers face when integrating artificial intelligence solutions into existing business systems?

AI Engineers often encounter challenges such as ensuring compatibility between new AI models and legacy systems, managing data quality and availability, and addressing scalability concerns. Effective communication with cross-functional teams, including data scientists, IT, and business stakeholders, is essential to understand requirements and mitigate potential roadblocks. Additionally, AI Engineers must balance innovation with ethical considerations and compliance, making it crucial to stay updated on industry standards and best practices.
What are popular job titles related to Ai In jobs in Iowa? For Ai In jobs in Iowa, the most frequently searched job titles are:
What job categories do people searching Ai In jobs in Iowa look for? The top searched job categories for Ai In jobs in Iowa are:
Ai In jobs near you
Infographic showing various Ai In job openings in Iowa as of May 2026, with employment types broken down into 4% Locum Tenens, 1% Internship, 41% Full Time, 11% Part Time, 4% Temporary, and 39% Contract. Highlights an 94% Physical, 1% Hybrid, and 5% Remote job distribution.

AI Developer

American technologies consulting

West Des Moines, IA • On-site

Contractor

Posted 8 days ago

Job description

Job Overview

We are seeking a skilled AI Developer to design, build, and deploy autonomous AI agents from scratch. This role involves creating intelligent systems that can perceive environments, make decisions, and execute actions in real-world or simulated scenarios. You will leverage machine learning, Python, and specialized frameworks like LangChain and LangGraph to develop scalable AI agents for applications such as automation, robotics, virtual assistants, or multi-agent simulations.

Key Responsibilities
  • Architect and implement AI agents from the ground up using frameworks such as LangChain for chaining LLMs and tools, and LangGraph for stateful, graph-based agent workflows, including perception modules (e.g., using computer vision or NLP), decision-making logic (e.g., via reinforcement learning or planning algorithms), and action execution components.
  • Develop and train machine learning models using frameworks like TensorFlow, PyTorch, or Scikit-learn to enable agent learning and adaptation, integrating with LangChain/LangGraph for advanced agent orchestration.
  • Integrate AI agents with external systems, APIs, databases, and environments (e.g., simulation tools like OpenAI Gym or real-world interfaces), ensuring seamless tool usage and memory management via LangChain components.
  • Optimize agents for performance, scalability, and robustness, including handling edge cases, ethical considerations, and safety protocols within graph-structured agent designs.
  • Collaborate with cross-functional teams (e.g., data scientists, software engineers) to iterate on agent designs based on feedback and testing.
  • Conduct experiments, simulations, and evaluations to refine agent behaviors and ensure reliability in production.
  • Document code, architectures, and methodologies for reproducibility and team knowledge sharing.
  • Stay current with advancements in AI agent technologies, such as large language models (LLMs), multi-agent systems, and emerging frameworks like LangChain and LangGraph.
Required Skills and Qualifications
  • Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
  • Proficiency in Python programming, with strong experience in ML libraries (e.g., TensorFlow, PyTorch, NumPy, Pandas) and agent-specific tools (e.g., LangChain, LangGraph, AutoGen, RLlib, Hugging Face Transformers).
  • Hands-on experience building AI agents from scratch using LangChain for tool integration and agent chains, LangGraph for multi-step reasoning and state management, including reinforcement learning, state machines, graph-based planning, or evolutionary algorithms.
  • Solid understanding of data structures, algorithms, software engineering principles, and version control (e.g., Git).
  • Familiarity with cloud platforms (e.g., AWS, Google Cloud, Azure) for deploying agents, and tools like Docker/Kubernetes for containerization.
  • Strong problem-solving skills, with the ability to debug complex systems and work in agile, fast-paced environments.
  • Excellent communication skills to articulate technical designs and collaborate effectively.
Preferred Qualifications
  • Experience with specialized domains like natural language processing (NLP), computer vision, robotics (e.g., ROS), or game AI, integrated with LangChain/LangGraph.
  • Knowledge of big data tools (e.g., Spark, Hadoop) or databases (SQL/NoSQL) for handling large-scale agent data.
  • Prior work with multi-agent systems, ethical AI, or real-time applications using advanced frameworks.
  • Contributions to open-source AI projects or a portfolio demonstrating agent-building expertise (e.g., GitHub repos showcasing LangChain/LangGraph implementations).