Design, build, and deploy intelligent agent-based systems using modern AI frameworks and cloud platforms to create scalable, adaptive, and collaborative AI solutions.
Requirements
- Hands-on experience with agent frameworks (e.g., Azure OpenAI, LangChain, Semantic Kernel).
- Experience with cloud platforms (Azure, AWS, Oracle Cloud) and containerization tools (Docker, Kubernetes).
- Strong understanding of AI concepts such as goal-directed behavior, planning, and reinforcement learning.
- Proficiency in Python; experience with JavaScript, Java, or C++ is a plus.
- Experience deploying multi-agent systems in production environments.
- Familiarity with agent communication protocols (e.g., FIPA ACL), semantic reasoning, and knowledge graphs.
- Exposure to LLM-based agent orchestration and prompt engineering.
Responsibilities
- Design and implement intelligent agents using frameworks such as Azure OpenAI, AWS Bedrock, Oracle AI, and open-source alternatives like LangChain or Semantic Kernel.
- Architect multi-agent systems capable of collaboration, negotiation, and autonomous task execution.
- Integrate agents with enterprise systems, APIs, and cloud services to enable real-world applications.
- Collaborate with AI researchers, software engineers, and product managers to define agent goals, behaviors, and interaction protocols.
- Optimize agent performance for scalability, responsiveness, and resource efficiency.
- Develop monitoring, logging, and debugging tools for agent-based systems.
- Stay current with advancements in agent-based modeling, reinforcement learning, and distributed AI systems.
Other
- Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, or a related field.
- 3+ years of experience in AI development, including at least 1 year focused on agent-based systems.
- Understanding of security, compliance, and ethical considerations in autonomous systems.
