Experience:

• 3 - 6 Years

Qualification:

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

Role Focus:

• Design and implement production-grade agentic architectures
• Build and optimise multi-agent systems
• Integrate external tools, APIs, and knowledge bases
• Tune agent performance
• Embed agentic AI into enterprise workflows
• Prototype advanced capabilities
• Contribute to code reviews, technical documentation, and team best practices

Nice to have:

• Exposure to MLOps practices
• Knowledge of distributed systems and scalable backend architectures
• Experience with cloud AI services on Azure, AWS, or GCP

More skills:

AI/ML framework experience, prompt engineering, fine-tuning (LoRA/QLoRA), agentic frameworks (LangChain, AutoGen, CrewAI), API integration, tool-augmented agent development, retrieval systems

Other:

• Technology->AI-AI Hyperscalers->Azure Agentic AI Services
• Technology->AI-AI Hyperscalers->Google Agentic AI Services
• Technology->AI-Agentic AI->Google Cloud –
• Technology->AI-AI Hyperscalers->AWS Agentic AI Services
• Technology->AI-Agentic AI->Agent Engineering
• Technology->AI-Agentic AI->AgentOps