AI Agent Developer

About the role

MCI is seeking an innovative AI Agent Developer to join our dynamic team. This role is focused on designing and building intelligent AI agents capable of automating tasks, orchestrating workflows, and enhancing business operations.

Responsibilities

• Develop intelligent agents that perform tasks, execute workflows, and interact with business systems.
• Design and build autonomous and semi-autonomous AI agents.
• Develop agent logic, memory, reasoning, and planning capabilities.
• Create agent workflows that automate complex business processes.
• Support multi-agent collaboration and orchestration solutions.
• Enable seamless interaction between AI agents and enterprise systems.
• Integrate agents with APIs, databases, and business applications.
• Build automated workflows across multiple platforms and technologies.
• Develop reusable tools and services that support agent functionality.
• Support enterprise-wide AI automation initiatives.
• Ensure AI agents operate efficiently, accurately, and reliably.
• Monitor agent performance and execution outcomes.
• Conduct testing, validation, and troubleshooting activities.
• Improve response quality, reliability, and task completion rates.
• Optimize agent workflows for scalability and efficiency.
• Drive innovation within AI agent development practices.
• Evaluate emerging agent frameworks and technologies.
• Research new approaches to AI automation and orchestration.
• Recommend enhancements to existing agent architectures.
• Contribute to AI best practices and knowledge-sharing initiatives.

Requirements

The ideal candidate should possess a Bachelor's Degree in Computer Science, Software Engineering, Information Technology, Artificial Intelligence, or a related field, with a minimum of 3 years of software development experience. Experience building AI-powered applications, intelligent systems, or workflow automation solutions is preferred. Strong proficiency in Python and API development is required, along with understanding of Large Language Models (LLMs) and Generative AI technologies. Experience integrating applications through APIs, web services, and third-party platforms is beneficial, as is knowledge of agent architectures, orchestration frameworks, and automation concepts. Experience designing scalable and maintainable software solutions is also important, as is understanding prompt engineering principles and AI workflow design. Familiarity with cloud platforms and deployment environments is advantageous, as is strong troubleshooting, analytical, and problem-solving skills. Excellent collaboration and communication abilities are essential, and experience with CrewAI, LangGraph, AutoGen, OpenAI Agents, or similar frameworks is a plus.

Qualifications

To be considered for this role, you must complete a full application on our company careers page, including all screening questions and a brief pre-employment test. No specific qualifications beyond those mentioned are required.

Skills

Strong proficiency in Python and API development.

Understanding of Large Language Models (LLMs) and Generative AI technologies.

Experience integrating applications through APIs, web services, and third-party platforms.

Knowledge of agent architectures, orchestration frameworks, and automation concepts.

Experience designing scalable and maintainable software solutions.

Understanding of prompt engineering principles and AI workflow design.

Familiarity with cloud platforms and deployment environments.

Strong troubleshooting, analytical, and problem-solving skills.

Excellent collaboration and communication abilities.

Nice to have:

• Experience with CrewAI, LangGraph, AutoGen, OpenAI Agents, or similar frameworks.
• Experience implementing Retrieval-Augmented Generation (RAG) architectures.
• Knowledge of vector databases and semantic search technologies.
• Experience with workflow automation platforms.
• Familiarity with Docker, Kubernetes, and containerized deployments.
• Understanding of AI governance and responsible AI principles.
• Experience building multi-agent systems.
• Exposure to MLOps and AI operations practices.