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

Role Focus:

• 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
• 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 (PyTorch, TensorFlow, or Scikit-learn), prompt engineering techniques, REST API integration, AutoGen, CrewAI

Other:

• Service Line: Engineering Services
• Responsible AI principles and safety considerations in LLM systems