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

- Good 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 Professional 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