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Assistant Ai Agent Developer Jobs in Iowa (NOW HIRING)

Lightedge

Sr. AI Integration Engineer

Des Moines, IA · On-site

$101K - $136K/yr

AI Agent, Harness & Workflow Development: Design, develop, and maintain production-grade AI agents ... Experience developing AI-powered assistants, copilots, or intelligent automation workflows used by ...

Accenture

Advanced AI Full Stack Engineer

Des Moines, IA · On-site

Our Data & AI practice brings together more than 45,000 professionals dedicated to helping clients ... agent code. SDK, API & Developer Tooling: * Build Python and Node.js/TypeScript SDKs and CLIs that ...

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Auzmor

Robotics & AI Research Engineer

Des Moines, IA · On-site

Robotics & AI Research Engineer Description Auzmor is redefining workforce training by seamlessly ... This role directly supports Auzmor's Phase 2 (2025) goals of launching AI agent training modules ...

Meta

IA

$193K/yr

Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies * Experience with network telemetry platforms ...

Kemin

Senior Software Engineer

Des Moines, IA · Hybrid

$119K - $157K/yr

Apply advanced prompt engineering to direct AI tools across code generation, debugging, refactoring, and documentation tasks; evaluate AI agent output for architectural fit and take responsibility ...

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Assistant Ai Agent Developer information

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

To thrive as an Assistant AI Agent Developer, you need a solid background in programming (especially Python), machine learning concepts, and a relevant degree in computer science or a related field. Familiarity with AI frameworks like TensorFlow or PyTorch, version control systems like Git, and APIs is typically required. Strong problem-solving abilities, attention to detail, and effective teamwork are essential soft skills for success in this role. These skills ensure the development of robust, efficient AI agents and smooth collaboration within multidisciplinary teams.

What are the typical collaboration practices for an Assistant AI Agent Developer within a software development team?

As an Assistant AI Agent Developer, you'll frequently collaborate with data scientists, senior developers, and product managers to design, test, and refine AI agents. You'll often participate in code reviews, daily standups, and brainstorming sessions to ensure that the AI solutions align with project goals and user needs. Effective communication and teamwork are essential, as you may need to integrate your code with other systems or adapt to evolving project requirements. Working with cross-functional teams not only helps in troubleshooting but also provides valuable learning opportunities to advance your skills.

What is an Assistant AI Agent Developer?

An Assistant AI Agent Developer is a professional who designs, develops, and maintains AI-powered virtual assistants or chatbot systems. Their work involves programming conversational agents, integrating natural language processing (NLP) technologies, and ensuring the agent can understand and respond to user queries effectively. They may also be responsible for training the AI using data, testing the assistant's performance, and deploying updates for improved accuracy and functionality. This role often requires knowledge of programming languages such as Python, familiarity with AI frameworks, and understanding of user experience design.
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AI Developer

American technologies consulting

West Des Moines, IA • On-site

Contractor

Re-posted 14 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).