Experience:

• 1 - 4 Years

Qualification:

• Bachelor of Engineering
• Bachelor Of Technology
• Bachelor Of Science
• Bachelor Of Comp. Applications
• Master Of Technology
• Master Of Engineering
• Master Of Comp. Applications
• Master Of Science

Responsibilities:

• Design and implement agentic architectures using LLMs and reasoning engines
• Develop multi-agent systems for task orchestration
• Integrate external tools, REST APIs, and knowledge bases to augment agent capabilities
• Write clean, well-documented Python code for agent logic and workflow components
• Support testing, evaluation, and debugging of agent pipelines
• Research agentic frameworks and prototype capabilities such as memory and planning modules
• Collaborate with cross-functional teams to embed agentic AI into business applications

Nice to have:

• Exposure to RAG (Retrieval-Augmented Generation) pipelines
• Familiarity with vector databases (Pinecone, Weaviate, Chroma)
• Basic knowledge of Docker and cloud environments (AWS, Azure, or GCP)

More skills:

AI/ML frameworks, agentic frameworks, REST API integration, agent augmentation, responsible AI principles, safety considerations in LLM systems, Docker, cloud environments, AWS, Azure, GCP, Agent Engineering, AgentOps, Azure Agentic AI Services, Google Agentic AI Services, AWS Agentic AI Services, Google Cloud –