Educational Requirements
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

Responsibilities
Design and implement production-grade agentic architectures leveraging LLMs and reasoning engines.
Build and optimise multi-agent systems for complex task orchestration and collaboration.
Integrate external tools, APIs, and knowledge bases for robust agent augmentation.
Tune agent performance for autonomy, adaptability, reliability, and safety.
Embed agentic AI into enterprise workflows in collaboration with product teams.
Prototype advanced capabilities: persistent memory, goal planning, and self-correction loops.
Contribute to code reviews, technical documentation, and team best practices.

Additional Responsibilities
Valuable to Have exposure to MLOps practices experiment tracking, model versioning (MLflow, DVC).
Knowledge of distributed systems and scalable backend architectures.




Experience with cloud AI services on Azure, AWS, or GCP.

Technical and Skilled Requirements
Solid Python programming with hands-on AI/ML framework experience.
Working knowledge of LLMs, prompt engineering, and basic fine-tuning (LoRA/QLoRA).
Practical experience with agentic frameworks such as LangChain, AutoGen, or CrewAI.
Experience with API integration and tool-augmented agent development.
Understanding of responsible AI, safety guardrails, and LLM evaluation strategies.
Familiarity with vector stores, retrieval systems, and RAG architectures.

Preferred Skills
Technology->AI-AI Hyperscalers->Azure Agentic AI Services
Technology->AI-AI Hyperscalers->Google Agentic AI Services
Technology->AI-Agentic AI->Google Cloud Contact Center AI
Technology->AI-AI Hyperscalers->AWS Agentic AI Services
Technology->AI-Agentic AI->Agent Engineering
Technology->AI-Agentic AI->AgentOps

📌 Agentic Ai Engineer Bengaluru
🏢 Infosys
📍 Bengaluru